Triple
T5468057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sima Samar |
E122761
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Sima |
E21586
|
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: Sima | Statement: [Sima Samar, givenName, Sima]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sima Context triple: [Sima Samar, givenName, Sima]
-
A.
Sima Samar
chosen
Sima Samar is an Afghan physician and human rights advocate renowned for her work promoting women's rights, education, and social justice in Afghanistan.
-
B.
Taishi
Taishi is a town in Osaka Prefecture, Japan, known for its historical sites and traditional rural character.
-
C.
Cai
Cai is a common Chinese surname shared by numerous individuals, including the contemporary artist Cai Guo-Qiang.
-
D.
Tumshuq
Tumshuq is an ancient city in the Tarim Basin region of Xinjiang, China, historically associated with the Saka (Scythian) peoples and their Eastern Iranian languages.
-
E.
Enlai
Enlai is the given name of Zhou Enlai, the prominent first Premier of the People's Republic of China and a key figure in Chinese Communist history.
- 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_69bd4643f16081908d7f29e08096115a |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd9218621c819093267a012bd49a35 |
completed | March 20, 2026, 6:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf70d919e08190a4fae4359cf8c951 |
completed | March 22, 2026, 4:32 a.m. |
Created at: March 20, 2026, 2:09 p.m.