Triple
T38044021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Atsumori |
E949565
|
entity |
| Predicate | featuresCharacterAsMonk |
P135775
|
FINISHED |
| Object | Kumagai Naozane |
E2282647
|
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: Kumagai Naozane | Statement: [Atsumori, featuresCharacterAsMonk, Kumagai Naozane]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresCharacterAsMonk Context triple: [Atsumori, featuresCharacterAsMonk, Kumagai Naozane]
-
A.
hasMonkCharacter
chosen
Indicates that an entity includes or features a character whose role or identity is that of a monk.
-
B.
typeOfMonk
Indicates that one entity is a specific kind or category of monk in relation to another entity.
-
C.
wasMonkOf
Indicates that a person was a member or monk belonging to a particular religious order, monastery, or monastic community.
-
D.
monkSince
Indicates the point in time since which an entity has held the status or role of a monk.
-
E.
relationshipToMonk
Indicates the specific type of relationship an entity has to a monk, such as familial, social, or institutional connection.
- F. None of above.
Provenance (4 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_69f76eff0bb0819084bc4e63997bd039 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037df1223c8190a5d61e4f8e6fd613 |
completed | May 12, 2026, 7:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a422ba3d0c481908c14bab1c86e1cfc |
completed | June 29, 2026, 8:24 a.m. |
| PD | Predicate disambiguation | batch_6a037a1ad6c48190bfe35d350c1b4751 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:20 p.m.