Triple
T11878734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saibai |
E282597
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Saibai |
E282597
|
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: Saibai | Statement: [Saibai, name, Saibai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saibai Context triple: [Saibai, name, Saibai]
-
A.
Saibai
chosen
Saibai was the first wife of Maratha ruler Shivaji and the mother of his son Sambhaji, the second Chhatrapati of the Maratha Empire.
-
B.
Saib
Saib is a character in Matthew Lewis's Gothic melodrama "The Castle Spectre," contributing to the play's dark, suspenseful atmosphere.
-
C.
Saiun
Saiun is the Allied reporting name for the Nakajima C6N, a fast and long-range Japanese carrier-based reconnaissance aircraft used during World War II.
-
D.
Sadaijin
Sadaijin was a high-ranking ministerial post in Japan’s imperial court, typically overseeing the left side of the government and ranking just below the chancellor in the classical ritsuryō system.
-
E.
Sairan
Sairan is a metro station on the Almaty Metro system in Almaty, Kazakhstan.
- 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_69d6ab2945d081908a5851c916cbcfb5 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8be1cad5c8190a45dfb0f0cc2a512 |
completed | April 10, 2026, 9:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f281d8c65081908ebaf4bff5670c47 |
completed | April 29, 2026, 10:10 p.m. |
Created at: April 8, 2026, 9:44 p.m.