Triple
T1369516
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Gray Lady |
E30079
|
entity |
| Predicate | colorReferenceExplains |
P27005
|
FINISHED |
| Object | conservative layout and typography of The New York Times |
—
|
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: conservative layout and typography of The New York Times | Statement: [The Gray Lady, colorReferenceExplains, conservative layout and typography of The New York Times]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: colorReferenceExplains Context triple: [The Gray Lady, colorReferenceExplains, conservative layout and typography of The New York Times]
-
A.
colors
Indicates that one entity assigns, describes, or provides the color or colors of another entity.
-
B.
colorationCause
Indicates that one entity is the cause or source of the coloration observed in another entity.
-
C.
colorOftenUsed
Indicates that a particular color is frequently used or commonly applied in relation to something.
-
D.
hasColorReference
Indicates that one entity serves as a reference or source for determining or specifying the color associated with another entity.
-
E.
colorVarietyOf
Indicates that one entity represents a specific color variant or color option of 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_69a498f912008190a376a98b207b2071 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c2d60fdc8190a9954b74ca2b2541 |
completed | March 1, 2026, 10:51 p.m. |
| PD | Predicate disambiguation | batch_69a4befb08b88190be966fa1aadd4bcd |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4bfc2134c81909cbaaa151d96e9a8 |
completed | March 1, 2026, 10:37 p.m. |
Created at: March 1, 2026, 7:57 p.m.