Triple
T12107161
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haya Harareet |
E288331
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Haya |
E42394
|
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: Haya | Statement: [Haya Harareet, givenName, Haya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Haya Context triple: [Haya Harareet, givenName, Haya]
-
A.
Haya
The Haya are a Bantu-speaking ethnic group of northwestern Tanzania, known for their advanced precolonial ironworking and intensive banana-based agriculture around Lake Victoria.
-
B.
Haya
chosen
Haya is a feminine given name of Arabic origin, commonly used in the Middle East and among Arabic-speaking communities.
-
C.
Haruna
Haruna was a Japanese Kongō-class fast battleship that served in the Imperial Japanese Navy during both World Wars and saw extensive action in the Pacific Theater.
-
D.
Haisyn
Haisyn is a city in central Ukraine known as a local administrative and economic center within Vinnytsia Oblast.
-
E.
Hieda
Hieda is a Japanese surname notably associated with historical and literary figures in classical Japanese records and folklore.
- 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_69d6ab4a5c448190a110d1273314b21a |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915632dc48190863e0239cef37e24 |
completed | April 10, 2026, 3:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f6795bf88190891acf918a432bef |
completed | May 2, 2026, 1:04 p.m. |
Created at: April 8, 2026, 9:49 p.m.