Triple
T25577943
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tees–Wear derby |
E641161
|
entity |
| Predicate | hasSupporterEmotion |
P170605
|
FINISHED |
| Object | highly passionate |
—
|
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: highly passionate | Statement: [Tees–Wear derby, hasSupporterEmotion, highly passionate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSupporterEmotion Context triple: [Tees–Wear derby, hasSupporterEmotion, highly passionate]
-
A.
hasSupporter
Indicates that one entity supports, endorses, or backs another entity.
-
B.
hasSupportersIn
Indicates that an entity is backed or endorsed by people or groups located within a specified place or region.
-
C.
hasSupporterDetail
Indicates that an entity is associated with specific information or attributes about a supporter related to it.
-
D.
supportsMood
Indicates that one entity helps maintain, enhance, or positively influence the emotional state or mood of another entity.
-
E.
requiresEmotion
Indicates that one entity’s occurrence, validity, or performance depends on the presence or experience of a particular emotion in another entity.
- 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_69e75dc281bc819095ec04dc0c3a94d0 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f693ffa7908190aa4c451b16df9be6 |
completed | May 3, 2026, 12:17 a.m. |
| PD | Predicate disambiguation | batch_69f690eb1e948190aab41a89969519a5 |
completed | May 3, 2026, 12:03 a.m. |
| PDg | Predicate description generation | batch_69f6938244648190a553b532387b812c |
completed | May 3, 2026, 12:14 a.m. |
Created at: April 21, 2026, 4:02 p.m.