Triple
T10642937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Finno-Ugric peoples |
E250767
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object |
Luds
Luds are a small Finno-Ugric ethnic group traditionally inhabiting parts of northwestern Russia, with their own Uralic language and distinct cultural traditions.
|
E877897
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Luds | Statement: [Finno-Ugric peoples, hasMember, Luds]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Luds Context triple: [Finno-Ugric peoples, hasMember, Luds]
-
A.
Ludes
Ludes is a wine-producing village in France’s Champagne region, known for its vineyards on the Montagne de Reims.
-
B.
Ludens
Ludens is the futuristic, spacesuit-clad mascot character of Kojima Productions, prominently featured in the studio’s branding and promotional materials.
-
C.
Lud
Lud is a decayed, trap-filled city in Stephen King’s The Dark Tower series, known for its warring factions, ancient technology, and pervasive atmosphere of ruin.
-
D.
LUD
LUD is the IATA airport code for Lüderitz Airport, a regional airport serving the coastal town of Lüderitz in Namibia.
-
E.
Ladurlad
Ladurlad is a central heroic figure in Robert Southey's epic poem "The Curse of Kehama," known for enduring a supernatural curse that renders him sleepless and invulnerable.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Luds Triple: [Finno-Ugric peoples, hasMember, Luds]
Generated description
Luds are a small Finno-Ugric ethnic group traditionally inhabiting parts of northwestern Russia, with their own Uralic language and distinct cultural traditions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Luds Target entity description: Luds are a small Finno-Ugric ethnic group traditionally inhabiting parts of northwestern Russia, with their own Uralic language and distinct cultural traditions.
-
A.
Ludes
Ludes is a wine-producing village in France’s Champagne region, known for its vineyards on the Montagne de Reims.
-
B.
Ludens
Ludens is the futuristic, spacesuit-clad mascot character of Kojima Productions, prominently featured in the studio’s branding and promotional materials.
-
C.
Lud
Lud is a decayed, trap-filled city in Stephen King’s The Dark Tower series, known for its warring factions, ancient technology, and pervasive atmosphere of ruin.
-
D.
LUD
LUD is the IATA airport code for Lüderitz Airport, a regional airport serving the coastal town of Lüderitz in Namibia.
-
E.
Ladurlad
Ladurlad is a central heroic figure in Robert Southey's epic poem "The Curse of Kehama," known for enduring a supernatural curse that renders him sleepless and invulnerable.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d6aa5a4c4881908f39be6efe5981e5 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6dfcf65fc81909a0c86daefaab1ab |
completed | April 8, 2026, 11:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d97a4555e48190be39c0a7698b4282 |
completed | April 10, 2026, 10:31 p.m. |
| NEDg | Description generation | batch_69d97cc07100819088683a0d79b2baa0 |
completed | April 10, 2026, 10:42 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d97e0cda0c8190af5013b971b2ad3c |
completed | April 10, 2026, 10:47 p.m. |
Created at: April 8, 2026, 9:05 p.m.