Triple
T36409337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haddonfield, Illinois |
E896833
|
entity |
| Predicate | timeOfPrimaryEvents |
P183544
|
FINISHED |
| Object | Halloween night |
—
|
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: Halloween night | Statement: [Haddonfield, Illinois, timeOfPrimaryEvents, Halloween night]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeOfPrimaryEvents Context triple: [Haddonfield, Illinois, timeOfPrimaryEvents, Halloween night]
-
A.
timeBetweenMainEvents
Indicates the duration or interval separating two primary or key events in a sequence or process.
-
B.
timeCoMainEvent
Indicates that two or more events occur as co-main events at the same time or within the same overarching event timeframe.
-
C.
timePeriodEvent
Indicates that an event occurs, is scheduled, or is valid within a specified time period.
-
D.
mainEventTime
chosen
Indicates the specific time at which the primary or central event occurs.
-
E.
timePeriodOfPrimaryStories
Indicates the time period during which the primary stories or main narrative events of something (e.g., a work or series) take place.
- 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_69f76e54ce408190849acc3f7758937c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fde49a084081909d99b1e0258169d5 |
completed | May 8, 2026, 1:26 p.m. |
| PD | Predicate disambiguation | batch_69fde1d04bd881909a46ecbbf18dfe59 |
completed | May 8, 2026, 1:14 p.m. |
Created at: May 3, 2026, 4:10 p.m.