Triple
T12178573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hadibu |
E290155
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object | Hadiboh |
E290155
|
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: Hadiboh | Statement: [Hadibu, hasAlternativeName, Hadiboh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hadiboh Context triple: [Hadibu, hasAlternativeName, Hadiboh]
-
A.
Hadibu
chosen
Hadibu is the main town and administrative center of the Yemeni island of Socotra in the Arabian Sea.
-
B.
Харабали
Харабали — город в Астраханской области России, расположенный на берегу реки Ахтубы и являющийся административным центром Харабалинского района.
-
C.
Dhiban
Dhiban is an archaeological site and modern town in Jordan, historically significant as the ancient Moabite city of Dibon.
-
D.
Larhat
Larhat is a coastal town and commune in northern Algeria, situated within Tipaza Province along the Mediterranean Sea.
-
E.
Hasbaya
Hasbaya is a historic town in southern Lebanon known for its strategic location near Mount Hermon and its traditional Druze and Christian communities.
- 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_69d6ab4d6c00819095a9a7c35de83cfb |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915fa6ff08190a1ddb3606c229cad |
completed | April 10, 2026, 3:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f6ab19288190a882c842d74a2e30 |
completed | May 2, 2026, 1:05 p.m. |
Created at: April 8, 2026, 9:50 p.m.