Triple
T7313370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lenakel |
E168148
|
entity |
| Predicate | hasNegationMarker |
P2130
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Lenakel, hasNegationMarker, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNegationMarker Context triple: [Lenakel, hasNegationMarker, true]
-
A.
hasMarker
chosen
Indicates that one entity possesses, is associated with, or is identified by a specific marker.
-
B.
hasCaseMarking
Indicates that a linguistic element (such as a noun or pronoun) bears a specific grammatical case marking that signals its syntactic or semantic role in a clause.
-
C.
negates
Indicates that one entity denies, contradicts, or renders false the assertion, state, or effect expressed by another.
-
D.
negativeMarking
Indicates that an entity assigns or receives a penalty, deduction, or unfavorable score in response to a particular action, performance, or condition.
-
E.
hasPersonMarkingOnVerb
Indicates that the verb carries explicit grammatical marking that identifies or agrees with the person (e.g., first, second, third person) of its subject or argument.
- 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_69c6888d8e3c81909db79714903baf31 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6ec02319c819096d25e3683943886 |
completed | March 27, 2026, 8:43 p.m. |
| PD | Predicate disambiguation | batch_69c6e7705f4881909793071dee50c557 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 3:02 p.m.