Triple
T36303903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hawkeye (2012) |
E893893
|
entity |
| Predicate | includesAnnual |
P204821
|
FINISHED |
| Object | Hawkeye Annual #1 |
E893893
|
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: Hawkeye Annual #1 | Statement: [Hawkeye (2012), includesAnnual, Hawkeye Annual #1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesAnnual Context triple: [Hawkeye (2012), includesAnnual, Hawkeye Annual #1]
-
A.
isAnnual
Indicates that something occurs, is scheduled, or is valid once every year.
-
B.
isAnnualClassOf
Indicates that one entity is the regularly recurring yearly instance or cohort of a particular class or course.
-
C.
hasAnnualList
Indicates that an entity maintains or is associated with a list that is updated or issued on an annual basis.
-
D.
isAnnualized
Indicates that a value has been converted or expressed on a yearly basis, typically by extrapolating from a shorter time period.
-
E.
annualFrom
Indicates that something recurs or is calculated on a yearly basis starting from a specified point in time.
- 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_69f76e4c1b248190b10667d0213537fe |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a397d842f1481908782c39664b5b68c |
completed | June 22, 2026, 6:23 p.m. |
| PD | Predicate disambiguation | batch_6a037a0a54cc8190868c1bfa1590d1a6 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82f8c88190bd77a086023ac0e1 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:09 p.m.