Triple
T12209729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ian Fletcher |
E290923
|
entity |
| Predicate | firstAppearanceInW1A |
P81018
|
FINISHED |
| Object | W1A, Series 1 Episode 1 |
—
|
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: W1A, Series 1 Episode 1 | Statement: [Ian Fletcher, firstAppearanceInW1A, W1A, Series 1 Episode 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstAppearanceInW1A Context triple: [Ian Fletcher, firstAppearanceInW1A, W1A, Series 1 Episode 1]
-
A.
firstAppearanceFor
Indicates that an entity marks the initial occurrence or debut of another entity within a given context or medium.
-
B.
firstPopularAppearance
Indicates the earliest notable or widely recognized appearance of an entity in a public or popular context.
-
C.
firstAppearanceApprox
Indicates that one entity is the approximate or estimated first appearance of another entity in time or context.
-
D.
firstAppearanceAct
chosen
Indicates the act in which an entity makes its first appearance within a work or performance.
-
E.
firstAppearanceMa
Indicates that an entity (such as a character or item) makes its first appearance in a specific manga.
- 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_69d6ab65923081909acfc61b7a612233 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d920e312708190b4aede2e21f5f697 |
completed | April 10, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69d91c3d669c81908eea7ad61122d275 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:51 p.m.