Triple
T29325297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Age IV |
E743624
|
entity |
| Predicate | hasSequenceRole |
P196283
|
FINISHED |
| Object | middle stage |
—
|
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: middle stage | Statement: [Age IV, hasSequenceRole, middle stage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSequenceRole Context triple: [Age IV, hasSequenceRole, middle stage]
-
A.
hasSequencePosition
Indicates that an element occupies a specific position or order within a sequence.
-
B.
usesSequence
Indicates that one entity employs or relies on a specific ordered sequence of elements, steps, or events in performing an action or defining a relationship.
-
C.
hasCharacterSequence
Indicates that one entity contains, exhibits, or follows a specific ordered sequence of characters.
-
D.
isSequence
Indicates that one entity is an ordered list or succession of elements arranged in a specific, meaningful order.
-
E.
hasOccupationSequenceTo
Indicates that one occupation in a person’s work history directly follows another in temporal sequence.
- 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_69f09125f784819080f4e9fce9fe624f |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69fe1fd637c08190aa95cd2478c278cb |
completed | May 8, 2026, 5:39 p.m. |
| PD | Predicate disambiguation | batch_69fe19344bb481909b5e2144155e4add |
completed | May 8, 2026, 5:11 p.m. |
| PDg | Predicate description generation | batch_69fe1fd58ad8819093d3d705e8521014 |
completed | May 8, 2026, 5:39 p.m. |
Created at: April 28, 2026, 1:26 p.m.