Triple
T6020429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shams-ud-Dīn |
E134048
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Shiraz |
E62427
|
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: Shiraz | Statement: [Shams-ud-Dīn, placeOfBirth, Shiraz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shiraz Context triple: [Shams-ud-Dīn, placeOfBirth, Shiraz]
-
A.
Shiraz
Shiraz is a dark-skinned wine grape variety, also known as Syrah, widely used to produce full-bodied red wines around the world.
-
B.
Shiraz, Iran
chosen
Shiraz, Iran is a historic city in southwestern Iran renowned for its rich Persian cultural heritage, poetry, gardens, and wine-making tradition.
-
C.
Shirazi
The Shirazi are a coastal East African ethnic group of mixed African and Persian ancestry, historically influential in the culture and Islamization of regions like Zanzibar.
-
D.
Kerman
Kerman is a small city in California’s San Joaquin Valley, known for its agricultural economy and location west of Fresno.
-
E.
Kerman
Kerman is a major city in southeastern Iran known for its rich history, traditional bazaars, and proximity to desert landscapes.
- 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_69c008742a5c8190b9cb9c2787a3d8b3 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04fba86a48190984e95d5adf7c7f1 |
completed | March 22, 2026, 8:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c108be2170819084b4b940e52b0185 |
completed | March 23, 2026, 9:32 a.m. |
Created at: March 22, 2026, 4:07 p.m.