Triple
T17945483
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Terrific |
E448691
|
entity |
| Predicate | firstAppearanceAsMichaelHoltYear |
P129834
|
FINISHED |
| Object | 1997 |
—
|
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: 1997 | Statement: [Mr. Terrific, firstAppearanceAsMichaelHoltYear, 1997]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstAppearanceAsMichaelHoltYear Context triple: [Mr. Terrific, firstAppearanceAsMichaelHoltYear, 1997]
-
A.
firstPublicationYearOfAppearance
Indicates the year in which an entity (such as a work or character) first appeared in a published form.
-
B.
firstAppearanceApprox
Indicates that one entity is the approximate or estimated first appearance of another entity in time or context.
-
C.
firstAppearanceFranchise
Indicates the franchise in which an entity made its first appearance.
-
D.
firstAppearanceMa
Indicates that an entity (such as a character or item) makes its first appearance in a specific manga.
-
E.
airDateOfFirstAppearance
Indicates the calendar date on which an entity (such as a character, show, or episode) was first broadcast or made publicly available.
- F. None of above. chosen
Provenance (4 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_69d8b9f8cca8819099836916c56b7c95 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4ad990b948190a5e6fd50a15f64e3 |
completed | April 19, 2026, 10:25 a.m. |
| PD | Predicate disambiguation | batch_69e3f8f2bd088190b1e22ad4d9cc8b13 |
completed | April 18, 2026, 9:34 p.m. |
| PDg | Predicate description generation | batch_69e42d8d68288190a05dc5d7803cf823 |
completed | April 19, 2026, 1:19 a.m. |
Created at: April 10, 2026, 10:21 a.m.