Triple
T10228641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lautém Municipality |
E243282
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Luro
Luro is an administrative post and rural area in eastern Timor-Leste known for its mountainous terrain and traditional villages.
|
E851164
|
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: Luro | Statement: [Lautém Municipality, contains, Luro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Luro Context triple: [Lautém Municipality, contains, Luro]
-
A.
Luri
Luri is a Southwestern Iranian language spoken primarily by the Lur people in western and southwestern Iran.
-
B.
Lules
Lules is a town in northwestern Argentina known for its agricultural production and proximity to the provincial capital of San Miguel de Tucumán.
-
C.
Luda
Luda is a nickname for Christopher Brian Bridges, better known as the American rapper and actor Ludacris.
-
D.
Luga
Luga is a small historic town in northwestern Russia known for its strategic location and role in regional transport and industry.
-
E.
Forlani
Forlani is an Italian surname most notably associated with English actress Claire Forlani.
- 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: Luro Triple: [Lautém Municipality, contains, Luro]
Generated description
Luro is an administrative post and rural area in eastern Timor-Leste known for its mountainous terrain and traditional villages.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Luro Target entity description: Luro is an administrative post and rural area in eastern Timor-Leste known for its mountainous terrain and traditional villages.
-
A.
Luri
Luri is a Southwestern Iranian language spoken primarily by the Lur people in western and southwestern Iran.
-
B.
Lules
Lules is a town in northwestern Argentina known for its agricultural production and proximity to the provincial capital of San Miguel de Tucumán.
-
C.
Luda
Luda is a nickname for Christopher Brian Bridges, better known as the American rapper and actor Ludacris.
-
D.
Luga
Luga is a small historic town in northwestern Russia known for its strategic location and role in regional transport and industry.
-
E.
Forlani
Forlani is an Italian surname most notably associated with English actress Claire Forlani.
- 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_69d381b0f97c819085c9b45799a5fb7c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d1fb93688190a9abcbebd9fede6c |
completed | April 7, 2026, 9:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6f72bc5388190a8337aa6a60ed51f |
completed | April 9, 2026, 12:47 a.m. |
| NEDg | Description generation | batch_69d6fa2bb2ec8190aa099988a6c225eb |
completed | April 9, 2026, 1 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d6fd10dbc08190a297073e1b737566 |
completed | April 9, 2026, 1:12 a.m. |
Created at: April 6, 2026, 11:18 a.m.