Triple
T343462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | W (Hollywood Sign letter) |
E6886
|
entity |
| Predicate | alphabetPosition |
P4901
|
FINISHED |
| Object | 23rd letter of the English alphabet |
—
|
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: 23rd letter of the English alphabet | Statement: [W (Hollywood Sign letter), alphabetPosition, 23rd letter of the English alphabet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alphabetPosition Context triple: [W (Hollywood Sign letter), alphabetPosition, 23rd letter of the English alphabet]
-
A.
ordinalNumber
chosen
Indicates the position or rank of an entity within an ordered sequence (e.g., first, second, third).
-
B.
letterSequence
Indicates that one sequence of letters directly follows or is ordered in relation to another within a larger string or alphabetic arrangement.
-
C.
alphabeticCode
Indicates that one entity is identified or represented by a specific alphabetic code assigned to it.
-
D.
namePosition
Indicates the positional or ordering relationship of a name within a sequence or structured context (e.g., first, last, or specific index).
-
E.
firstLetter
Indicates that one entity is the initial character or starting letter of another entity (typically a string or word).
- 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.