Triple
T6643412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abu Hanifa |
E150640
|
entity |
| Predicate | birthPlace |
P1
|
FINISHED |
| Object | Kufa |
E47842
|
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: Kufa | Statement: [Abu Hanifa, birthPlace, Kufa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kufa Context triple: [Abu Hanifa, birthPlace, Kufa]
-
A.
Kufa
chosen
Kufa is an ancient Iraqi city that became an early Islamic cultural and religious center, historically renowned as a hub of scholarship and calligraphy.
-
B.
Hamina
Hamina is a coastal town and municipality in southeastern Finland known for its historic star-shaped fortress and strategic location on the Gulf of Finland.
-
C.
Tarhuna
Tarhuna is a town in northwestern Libya, southeast of Tripoli, known for its strategic role and tribal influence during the Libyan civil conflicts.
-
D.
Marsa al-Brega
Marsa al-Brega is a coastal industrial town in northeastern Libya known for its major oil refinery and petrochemical facilities on the Gulf of Sidra.
-
E.
Tanta
Tanta is a major city in northern Egypt that serves as an important commercial and transportation hub in the Nile Delta.
- 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_69c687f1a3048190828b7342f7125d5c |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6aff749d48190bf24d448daf13bc7 |
completed | March 27, 2026, 4:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6eeef3f7481909929838858225f41 |
completed | March 27, 2026, 8:56 p.m. |
Created at: March 27, 2026, 2 p.m.