Triple
T15494596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ebrahim Afshar |
E378781
|
entity |
| Predicate | occupation |
P3
|
FINISHED |
| Object | shah |
E365310
|
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: shah | Statement: [Ebrahim Afshar, occupation, shah]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: shah Context triple: [Ebrahim Afshar, occupation, shah]
-
A.
Shah
chosen
Shah is a royal title historically used for monarchs and rulers in Persia (Iran) and other regions of the Islamic world.
-
B.
ŠA
ŠA is the regional vehicle registration code used on license plates for the city of Šabac in Serbia.
-
C.
Shahi
Shahi is a surname of Persian origin most notably borne by American actress Sarah Shahi.
-
D.
Sharafat
Sharafat is an Indian film for which Kamal Bose is particularly recognized for his acclaimed cinematography work.
-
E.
Sharaf
Sharaf is a novel by Egyptian writer Sonallah Ibrahim that offers a sharp critique of social and political corruption in contemporary Egypt.
- 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_69d85cd53a7c819080f5b9042c4c199e |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03faecd60819091eeaa56c9c8f67d |
completed | April 16, 2026, 1:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3662f3388190b75ffe3ce418f36d |
completed | May 9, 2026, 1:28 p.m. |
Created at: April 10, 2026, 3:49 a.m.