Triple
T4904558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shepherd of Hermas |
E109882
|
entity |
| Predicate | numberOfMandates |
P60570
|
FINISHED |
| Object | 12 |
—
|
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: 12 | Statement: [Shepherd of Hermas, numberOfMandates, 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMandates Context triple: [Shepherd of Hermas, numberOfMandates, 12]
-
A.
numberOfElectedMembers
Indicates the total count of individuals who have been formally chosen through an election to serve as members of a given body or group.
-
B.
numberOfLegislatures
Indicates the total count of distinct legislatures associated with or relevant to a given entity.
-
C.
numberOfSenates
Indicates the total count of senate bodies associated with or present in a given context or entity.
-
D.
numberOfSeatsWon
Indicates the quantity of seats secured by an entity (such as a party or candidate) in an election or representative body.
-
E.
numberOfColoniesRepresented
Indicates the count of distinct colonies that are represented or involved in relation to a given entity or context.
- 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_69bd441180708190ba42ffb44fea533a |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd706245e48190a61d573438461c30 |
completed | March 20, 2026, 4:05 p.m. |
| PD | Predicate disambiguation | batch_69bd6c306b188190a08a7856beb76db4 |
completed | March 20, 2026, 3:48 p.m. |
| PDg | Predicate description generation | batch_69bd7060f9988190afdf98eb0a38515d |
completed | March 20, 2026, 4:05 p.m. |
Created at: March 20, 2026, 1:29 p.m.