Triple
T343444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | W (Hollywood Sign letter) |
E6886
|
entity |
| Predicate | positionInWord |
P5131
|
FINISHED |
| Object | first letter of "WOOD" in "HOLLYWOOD" |
—
|
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: first letter of "WOOD" in "HOLLYWOOD" | Statement: [W (Hollywood Sign letter), positionInWord, first letter of "WOOD" in "HOLLYWOOD"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: positionInWord Context triple: [W (Hollywood Sign letter), positionInWord, first letter of "WOOD" in "HOLLYWOOD"]
-
A.
positionOn
Indicates that one entity is located on top of or at a specific place along the surface or extent of another entity.
-
B.
isPositionOf
Indicates that one entity represents the spatial or organizational position or location of another entity.
-
C.
positionB
Indicates that one entity occupies or is located at a specific position relative to another entity.
-
D.
positionInHebrewBible
Indicates the ordinal position that something occupies within the canonical sequence of books or passages in the Hebrew Bible.
-
E.
positionA
chosen
Indicates the spatial or ordered position of an entity A within a defined reference frame or sequence.
- 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_69a2e7951ba08190960e90823b5078f3 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eb0019088190a9b969c4287dc4fa |
completed | Feb. 28, 2026, 1:17 p.m. |
| PD | Predicate disambiguation | batch_69a2e9530c98819085025efe4e04aa7e |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.