Triple
T13223004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Labayu |
E314801
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Labayu |
E314801
|
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: Labayu | Statement: [Labayu, name, Labayu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Labayu Context triple: [Labayu, name, Labayu]
-
A.
Labayu
chosen
Labayu was a 14th-century BCE Canaanite ruler known from the Amarna letters for his aggressive expansionism and conflicts with neighboring city-states.
-
B.
Ayubia
Ayubia is a popular hill resort and national park area in Pakistan’s Galyat region, known for its cool climate, pine forests, and scenic chairlift.
-
C.
Guática
Guática is a small municipality and town in the Colombian department of Risaralda, known for its rural Andean landscapes and coffee-growing economy.
-
D.
Azoyú
Azoyú is a small town and municipal seat in the Costa Chica region of the Mexican state of Guerrero, known for its rural character and coastal cultural traditions.
-
E.
Bawi
Bawi was a Sasanian Persian military commander known for leading forces against the Byzantine Empire during the Iberian War in the 6th century.
- 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_69d806affc688190a25b6ccc588e9c72 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf74d708190a61d8ad938653b06 |
completed | April 10, 2026, 11:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f716c4a71c8190b0e0ae40af115c64 |
completed | May 3, 2026, 9:35 a.m. |
Created at: April 9, 2026, 9:19 p.m.