Triple
T5468044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samar |
E122761
|
entity |
| Predicate | usedBy |
P260
|
FINISHED |
| Object | Sima Samar |
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 Samar | Statement: [Samar, usedBy, Sima Samar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sima Samar Context triple: [Samar, usedBy, Sima Samar]
-
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.
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.
-
C.
Sasima
Sasima was an obscure town in ancient Cappadocia, best known as the short-lived and reluctant episcopal see of Gregory of Nazianzus in the 4th century.
-
D.
Sarpanit
Sarpanit is a Mesopotamian goddess, chiefly known as the consort of the Babylonian god Marduk and associated with fertility and motherhood.
-
E.
Shimsha
Shimsha is a river in southern India that flows through Karnataka and is known for its waterfalls and contribution to the Kaveri river system.
- 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_69bf48903dc48190b4e5a0c22545d6cc |
completed | March 22, 2026, 1:40 a.m. |
Created at: March 20, 2026, 2:09 p.m.