Triple
T3751066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nicias |
E81328
|
entity |
| Predicate | religiousReputation |
P33575
|
FINISHED |
| Object | pious |
—
|
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: pious | Statement: [Nicias, religiousReputation, pious]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religiousReputation Context triple: [Nicias, religiousReputation, pious]
-
A.
religiousCharacteristic
chosen
Indicates that one entity has a religious attribute, quality, or affiliation that characterizes or distinguishes it in a religious context.
-
B.
religiousTarget
Indicates that an action, policy, or behavior is directed at someone or something specifically because of their religion or religious affiliation.
-
C.
religiousElement
Indicates that something is a component, aspect, or feature associated with a religion or religious practice.
-
D.
religiousAffiliation
Indicates that one entity has a specified religious association, belief system, or denominational membership.
-
E.
bearerReligion
Indicates that a bearer (such as a person or entity) adheres to, practices, or is associated with a particular religion.
- F. None of above.
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_69ad8b19b7b08190a6188804e99c53e9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb909bb4819088559f90d718f72f |
completed | March 8, 2026, 7:18 p.m. |
| PD | Predicate disambiguation | batch_69adc04adebc819088d7f36d0ac343a6 |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:35 p.m.