Triple
T1629988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Halloween Time at the Disneyland Resort |
E35234
|
entity |
| Predicate | typicallyStartsIn |
P12625
|
FINISHED |
| Object | September |
—
|
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: September | Statement: [Halloween Time at the Disneyland Resort, typicallyStartsIn, September]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicallyStartsIn Context triple: [Halloween Time at the Disneyland Resort, typicallyStartsIn, September]
-
A.
startsAt
Indicates that an event, process, or state begins at a specific time, location, or point in a sequence.
-
B.
typicalStartSeason
chosen
Indicates the season during which something (such as an activity, event, or phenomenon) usually begins.
-
C.
beganInYear
Indicates that an event, process, or state started in a specific calendar year.
-
D.
startDate
Indicates the point in time when an event, state, or relationship begins.
-
E.
inceptionDate
Indicates the date on which an entity, event, or relationship was first created, established, or began to exist.
- 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_69a886036bc081909ff5de16dbe5e8ea |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a9431af5ac8190893133f1ae490142 |
completed | March 5, 2026, 8:47 a.m. |
| PD | Predicate disambiguation | batch_69a907c91c888190b6ed295c1a2e0977 |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:28 p.m.