Triple
T28754494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gongsun Zan |
E731628
|
entity |
| Predicate | loyaltyClaim |
P165285
|
FINISHED |
| Object | nominally loyal to the Han emperor |
—
|
LITERAL 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: nominally loyal to the Han emperor | Statement: [Gongsun Zan, loyaltyClaim, nominally loyal to the Han emperor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: loyaltyClaim Context triple: [Gongsun Zan, loyaltyClaim, nominally loyal to the Han emperor]
-
A.
loyaltyReason
Indicates the reason or motivation behind one entity’s loyalty or allegiance to another.
-
B.
loyaltySymbolizedBy
Indicates that an instance of loyalty is represented or expressed by a particular symbol or emblem.
-
C.
loyaltyRevealedIn
Indicates that an entity’s loyalty becomes evident or is demonstrated through a particular situation, action, or context.
-
D.
loyaltyIncentive
Indicates a relationship where benefits or rewards are provided to encourage or recognize continued commitment or repeat engagement.
-
E.
loyaltyIntegration
Indicates the degree to which a loyalty or rewards program is connected, synchronized, or functionally embedded with another system, platform, or service.
- F. None of above. chosen
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_69f043ed68a881909e858a06bab7a247 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f657f9d5248190b6f3f82f20f069a3 |
completed | May 2, 2026, 8 p.m. |
| PD | Predicate disambiguation | batch_69f651ada6048190a7b4a6981565dc3a |
completed | May 2, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69f6562ef4e4819082ce6abd41b74dc5 |
completed | May 2, 2026, 7:53 p.m. |
Created at: April 28, 2026, 6:09 a.m.