Triple
T6356493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lexington Avenue Express (5) |
E143004
|
entity |
| Predicate | letterOrNumberDesignation |
P70157
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [Lexington Avenue Express (5), letterOrNumberDesignation, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: letterOrNumberDesignation Context triple: [Lexington Avenue Express (5), letterOrNumberDesignation, 5]
-
A.
hasLetterDesignation
Indicates that an entity is assigned or associated with a specific letter-based designation or code.
-
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.
hasLetter
Indicates that one entity contains, includes, or is associated with a specific letter or character.
-
D.
isLetterSeat
Indicates that a given seat is designated as a lettered seat (identified by a letter rather than a number or other label).
-
E.
designatorType
Indicates the specific role or category of a designator used to identify or reference an entity within a system or context.
- 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_69c008d7a9c4819098d647ec47776917 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c067f37d0881909289bafb09e29298 |
completed | March 22, 2026, 10:06 p.m. |
| PD | Predicate disambiguation | batch_69c060ec091c8190912aac44e1b8b1c9 |
completed | March 22, 2026, 9:36 p.m. |
| PDg | Predicate description generation | batch_69c0623bb29081908bfdfb84a07ece90 |
completed | March 22, 2026, 9:42 p.m. |
Created at: March 22, 2026, 4:32 p.m.