Triple
T35419731
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeffrey Skiles |
E1023747
|
entity |
| Predicate | notableEventOrigin |
P206974
|
FINISHED |
| Object | LaGuardia Airport |
E9979
|
NE 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: LaGuardia Airport | Statement: [Jeffrey Skiles, notableEventOrigin, LaGuardia Airport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableEventOrigin Context triple: [Jeffrey Skiles, notableEventOrigin, LaGuardia Airport]
-
A.
notableEventMentionedIn
Indicates that a particular notable event is referenced or discussed within a specified source or document.
-
B.
notableEventResponse
Indicates a response, reaction, or consequence that occurs as a result of a notable event.
-
C.
notableEventIncluded
Indicates that a particular notable event is contained within, or forms part of, a larger collection, record, or context.
-
D.
notableAIEvent
Indicates that an event is recognized as significant or influential within the field of artificial intelligence.
-
E.
notableStoryEvent
Indicates that an event plays a significant or memorable role within the narrative or storyline associated with the subject.
- F. None of above. chosen
Provenance (5 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_69f76df6704081909900c60be10d5849 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3836b3b03c819094bcb32130a37495 |
completed | June 21, 2026, 7:08 p.m. |
| PD | Predicate disambiguation | batch_6a037a0324d08190ac5b610cc0f6a38c |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82179081908325a59b8539b3a8 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:03 p.m.