Triple
T14889447
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lahej Sultanate |
E359714
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Lahej |
E1085219
|
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: Lahej | Statement: [Lahej Sultanate, capital, Lahej]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lahej Context triple: [Lahej Sultanate, capital, Lahej]
-
A.
Lahej
chosen
Lahej was a former sultanate in southern Arabia that later became part of the British-influenced Federation of South Arabian states.
-
B.
Larhat
Larhat is a coastal town and commune in northern Algeria, situated within Tipaza Province along the Mediterranean Sea.
-
C.
Larevat
Larevat is an Oceanic language spoken in Vanuatu, closely related to and geographically near the Uripiv-Wala-Rano-Atchin language cluster.
-
D.
Leheriya
Leheriya is a traditional Indian tie-dye textile technique from Rajasthan, characterized by its distinctive diagonal wave-like patterns in vibrant colors.
-
E.
Lapseki
Lapseki is a town and district in Çanakkale Province in northwestern Turkey, situated on the Asian shore of the Dardanelles Strait.
- 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_69d827980cbc8190a0c569ae3940a1d9 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69ded5f6cf5c8190b6b28f58fafe5d59 |
completed | April 15, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe6b61407481908a618d14c56d2abf |
completed | May 8, 2026, 11:01 p.m. |
Created at: April 10, 2026, 2:09 a.m.