Triple
T12481297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London Town |
E298311
|
entity |
| Predicate | hasIntendedMood |
P63081
|
FINISHED |
| Object | chill |
—
|
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: chill | Statement: [London Town, hasIntendedMood, chill]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIntendedMood Context triple: [London Town, hasIntendedMood, chill]
-
A.
hasMood
Indicates that an entity is experiencing or characterized by a particular emotional or affective state.
-
B.
hasMoodSystem
Indicates that an entity possesses or is associated with a system responsible for managing or representing moods or emotional states.
-
C.
intendedEmotion
chosen
Indicates the emotion that an action, expression, or communication is meant to evoke in its target, regardless of the actual emotion experienced.
-
D.
hasMoodCategory
Indicates that an entity is associated with a particular mood classification or emotional category.
-
E.
supportsMood
Indicates that one entity helps maintain, enhance, or positively influence the emotional state or mood of another entity.
- 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_69d6ada377208190a36011199a4d8558 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94e8a706c8190873623eab7db607d |
completed | April 10, 2026, 7:24 p.m. |
| PD | Predicate disambiguation | batch_69d94d41f3cc8190a3331fb9a895306f |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:56 p.m.