Triple
T29132657
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lexington Avenue between 25th and 26th Streets |
E738420
|
entity |
| Predicate | hasLandmarkEvent |
P2107
|
FINISHED |
| Object | 1913 Armory Show |
—
|
NE NERFINISHED |
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: 1913 Armory Show | Statement: [Lexington Avenue between 25th and 26th Streets, hasLandmarkEvent, 1913 Armory Show]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLandmarkEvent Context triple: [Lexington Avenue between 25th and 26th Streets, hasLandmarkEvent, 1913 Armory Show]
-
A.
isLandmarkEvent
Indicates that an event is recognized as a significant or notable occurrence, often marking an important milestone or turning point.
-
B.
hasHistoricalEvent
chosen
Indicates that a historical event occurred in, is associated with, or is relevant to a particular entity.
-
C.
hasNotablePersonEvent
Indicates that there exists a significant event in which the person plays a notable or central role.
-
D.
hasNamesakeNotableEvent
Indicates that one entity serves as the namesake for a notable event associated with the other entity.
-
E.
hasNearbyHistoricalEvent
Indicates that a given entity is located close to the site where a specific historical event occurred.
- 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_69f07cb3adb48190a9e0e169cd026634 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69fd389cb28c819099a77e28d25f258a |
completed | May 8, 2026, 1:13 a.m. |
| PD | Predicate disambiguation | batch_69fd3826d8048190ada79a5868d1d7f3 |
completed | May 8, 2026, 1:11 a.m. |
Created at: April 28, 2026, 11:32 a.m.