Triple
T33549976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ward–Gatti III |
E859305
|
entity |
| Predicate | attireColorOfMickyWard |
P177423
|
FINISHED |
| Object | green and white trunks |
—
|
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: green and white trunks | Statement: [Ward–Gatti III, attireColorOfMickyWard, green and white trunks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: attireColorOfMickyWard Context triple: [Ward–Gatti III, attireColorOfMickyWard, green and white trunks]
-
A.
colorAssociatedWithCostume
Indicates that a particular color is thematically or typically linked to a specific costume.
-
B.
wearsUniformColor
Indicates that an entity regularly uses or is associated with a specific uniform color as part of its standard attire or dress code.
-
C.
dressColor
Indicates the color attribute associated with a particular dress.
-
D.
wearsColorFrequently
Indicates that an entity regularly and habitually wears items of a particular color.
-
E.
suitColor
Indicates that one entity has or is associated with a particular color of suit.
- 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_69f3497a5be08190a39b12736899e034 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6fb93224881908fc66fe76115fcdb |
completed | May 3, 2026, 7:38 a.m. |
| PD | Predicate disambiguation | batch_69f6f96badb08190994442c2aba840b1 |
completed | May 3, 2026, 7:29 a.m. |
| PDg | Predicate description generation | batch_69f6fb17d5ec81909091e37e1ddbe577 |
completed | May 3, 2026, 7:36 a.m. |
Created at: May 1, 2026, 1:39 a.m.