Triple
T27158432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Why You Wanna Trip on Me |
E682588
|
entity |
| Predicate | secondaryMood |
P181039
|
FINISHED |
| Object | defensive |
—
|
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: defensive | Statement: [Why You Wanna Trip on Me, secondaryMood, defensive]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondaryMood Context triple: [Why You Wanna Trip on Me, secondaryMood, defensive]
-
A.
secondaryEmotion
Indicates that one emotion arises as a secondary, derivative, or reactive feeling in response to a primary emotion.
-
B.
secondaryTone
Indicates that one tone functions as a secondary or supporting tonal element in relation to a primary tone within a given context.
-
C.
secondaryTo
Indicates that one condition, event, or factor occurs as a consequence of, or is caused by, another primary condition, event, or factor.
-
D.
secondarySee
Indicates that one entity is referenced as an additional or alternative point of consultation or viewing in relation to another entity.
-
E.
secondaryState
Indicates that an entity is in a subordinate or less primary condition, status, or mode relative to its main or primary state.
- 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_69eefaceb2a08190b9659b7f730629f5 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f760a35b988190904e6267553ad2fe |
completed | May 3, 2026, 2:50 p.m. |
| PD | Predicate disambiguation | batch_69f75eb3d6f081908c933474eb359e3d |
completed | May 3, 2026, 2:41 p.m. |
| PDg | Predicate description generation | batch_69f760a2a90c8190b8fbc55412ab752b |
completed | May 3, 2026, 2:50 p.m. |
Created at: April 27, 2026, 9:17 a.m.