Triple
T6202982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jebel Barkal |
E138679
|
entity |
| Predicate | nearbySitesInclude |
P19575
|
FINISHED |
| Object | Sanam |
E565569
|
NE FINISHED |
How this triple was built (2 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: Sanam | Statement: [Jebel Barkal, nearbySitesInclude, Sanam]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sanam Context triple: [Jebel Barkal, nearbySitesInclude, Sanam]
-
A.
Sanam
chosen
Sanam is an archaeological site in Sudan’s Napatan region, known for its ancient Kushite remains and its inclusion in the UNESCO-listed Gebel Barkal and associated sites.
-
B.
Sairat
Sairat is a critically acclaimed and commercially successful Marathi romantic drama film known for its powerful portrayal of caste and class conflict in rural India.
-
C.
Kareen
Kareen is a feminine given name, typically considered a variant spelling of names like Carine or Karen.
-
D.
Jeena
Jeena is the central protagonist of the Indian television series "Good Vibes."
-
E.
Sanjna
Sanjna is a figure in Hindu mythology known as the wife of the sun god Surya and the daughter of the god of justice, often associated with themes of devotion and transformation.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c008acbea48190991c6b834bb45d65 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0626a32908190a3332008aee2e4a9 |
completed | March 22, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c16f3bad2c8190b0ad0f2def3af9f7 |
completed | March 23, 2026, 4:50 p.m. |
Created at: March 22, 2026, 4:20 p.m.