Triple
T30673178
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baxter Building |
E780846
|
entity |
| Predicate | firstAppearanceApproxYear |
P121574
|
FINISHED |
| Object | 1962 |
—
|
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: 1962 | Statement: [Baxter Building, firstAppearanceApproxYear, 1962]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstAppearanceApproxYear Context triple: [Baxter Building, firstAppearanceApproxYear, 1962]
-
A.
firstAppearanceApprox
Indicates that one entity is the approximate or estimated first appearance of another entity in time or context.
-
B.
firstPublicationYearOfAppearance
Indicates the year in which an entity (such as a work or character) first appeared in a published form.
-
C.
firstAppearedAt
Indicates the point in time or specific event at which an entity was first introduced, observed, or became known.
-
D.
yearOfFirstApparition
chosen
Indicates the calendar year in which the entity first appeared or was introduced.
-
E.
timePeriodOfFirstAppearance
Indicates the time period during which something first appeared or was initially introduced.
- 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_69f224a7fc208190a07d6d3879b31640 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a030e31e01881909c6032532cd3c31a |
completed | May 12, 2026, 11:25 a.m. |
| PD | Predicate disambiguation | batch_6a030dadea008190abe0a5652784bdd6 |
completed | May 12, 2026, 11:23 a.m. |
Created at: April 29, 2026, 8:32 p.m.