Triple
T30750705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montgomery Allen |
E782947
|
entity |
| Predicate | hasYearOfFirstAppearance |
P121574
|
FINISHED |
| Object | 2023 |
—
|
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: 2023 | Statement: [Montgomery Allen, hasYearOfFirstAppearance, 2023]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasYearOfFirstAppearance Context triple: [Montgomery Allen, hasYearOfFirstAppearance, 2023]
-
A.
yearOfFirstApparition
chosen
Indicates the calendar year in which the entity first appeared or was introduced.
-
B.
workDateOfFirstAppearance
Indicates the date on which a work first appeared, was released, or was made publicly available.
-
C.
airDateOfFirstAppearance
Indicates the calendar date on which an entity (such as a character, show, or episode) was first broadcast or made publicly available.
-
D.
ageInFirstAppearance
Indicates the age an entity was when it first appeared or was initially introduced in a given context.
-
E.
firstPublicationYearOfAppearance
Indicates the year in which an entity (such as a work or character) first appeared in a published form.
- 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_69f224af8d8481908bea03890c5618be |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f68f911bf4819093102cd020a925e8 |
completed | May 2, 2026, 11:58 p.m. |
| PD | Predicate disambiguation | batch_69f686140aa08190a35f62572b2db9b6 |
completed | May 2, 2026, 11:17 p.m. |
Created at: April 29, 2026, 8:39 p.m.