Triple
T4904559
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shepherd of Hermas |
E109882
|
entity |
| Predicate | numberOfSimilitudes |
P42152
|
FINISHED |
| Object | 10 |
—
|
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: 10 | Statement: [Shepherd of Hermas, numberOfSimilitudes, 10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSimilitudes Context triple: [Shepherd of Hermas, numberOfSimilitudes, 10]
-
A.
isIsomorphicTo
Indicates that two structures have a one-to-one, structure-preserving correspondence between their elements, making them equivalent in form even if not identical in content.
-
B.
numberOfReconstructions
Indicates the count of times an entity has been reconstructed or rebuilt.
-
C.
localSymmetry
Indicates that an entity exhibits symmetry within a localized region or subset of its structure, rather than across its entire extent.
-
D.
numberOfCounts
chosen
Indicates the total quantity or tally of discrete occurrences, items, or instances associated with an entity or event.
-
E.
numberOfSees
Indicates the count of times a seeing or viewing event occurs between entities.
- 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_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. |
Created at: March 20, 2026, 1:29 p.m.