Triple
T10009054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Short People |
E198323
|
entity |
| Predicate | hasCounterVerse |
P85011
|
FINISHED |
| Object | later verses undercut the bigoted narrator |
—
|
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: later verses undercut the bigoted narrator | Statement: [Short People, hasCounterVerse, later verses undercut the bigoted narrator]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCounterVerse Context triple: [Short People, hasCounterVerse, later verses undercut the bigoted narrator]
-
A.
containsCounterpoint
chosen
Indicates that one element includes or incorporates another element that serves as a contrasting or opposing argument, idea, or perspective.
-
B.
hasCounterpart
Indicates that one entity corresponds to, matches, or serves as an equivalent or parallel version of another entity.
-
C.
hasCounterexample
Indicates that there exists at least one specific case or instance that disproves or violates a given claim, rule, or general statement.
-
D.
hasVerseCount
Indicates that an entity (such as a text or section) is associated with a specific number of verses it contains.
-
E.
verses
Indicates a relationship where one entity competes or is pitted against another, as in an opposition, matchup, or comparison.
- 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_69ca830fcca48190bbbd9b20c233835f |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cdcd38659c8190830d223edbfd74ec |
completed | April 2, 2026, 1:58 a.m. |
| PD | Predicate disambiguation | batch_69cd1da2cf9081908a6c0eb5247d0bc2 |
completed | April 1, 2026, 1:29 p.m. |
Created at: March 30, 2026, 8:52 p.m.