Triple
T10197620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Michael Tyler |
E238802
|
entity |
| Predicate | hairColorOfFamousCharacter |
P92646
|
FINISHED |
| Object | bleached blond |
—
|
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: bleached blond | Statement: [James Michael Tyler, hairColorOfFamousCharacter, bleached blond]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hairColorOfFamousCharacter Context triple: [James Michael Tyler, hairColorOfFamousCharacter, bleached blond]
-
A.
hairColorInFiction
Indicates that a fictional character is depicted as having a particular hair color within a narrative or fictional context.
-
B.
hairColorAsCharly
Indicates that one entity has the same hair color as the reference entity "Charly."
-
C.
hairColorOnScreen
Indicates the hair color that an entity appears to have when shown or rendered on a screen.
-
D.
depictsHairColor
Indicates that one entity visually represents or portrays the hair color of another entity.
-
E.
hairAsSymbol
Indicates that hair functions as a symbolic element representing ideas, traits, or meanings beyond its literal physical presence.
- 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_69ca84e1ea088190b38162e43d4cfa8f |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdee3c44408190b09fa41f2d257c04 |
completed | April 2, 2026, 4:19 a.m. |
| PD | Predicate disambiguation | batch_69cd7c8477648190bc55c56aeec507d3 |
completed | April 1, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69cd7edc6cf081909d95859d880a4059 |
completed | April 1, 2026, 8:23 p.m. |
Created at: March 30, 2026, 9:13 p.m.