Triple
T10000260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fort Griffith |
E197306
|
entity |
| Predicate | firstAppearanceFormat |
P74890
|
FINISHED |
| Object | television episode |
—
|
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: television episode | Statement: [Fort Griffith, firstAppearanceFormat, television episode]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstAppearanceFormat Context triple: [Fort Griffith, firstAppearanceFormat, television episode]
-
A.
firstAppearanceType
chosen
Indicates the type or category of context (e.g., medium, format, or work) in which an entity makes its first recorded appearance.
-
B.
firstAppearanceFor
Indicates that an entity marks the initial occurrence or debut of another entity within a given context or medium.
-
C.
firstAppearancePublisher
Indicates the publisher responsible for releasing an entity’s first appearance.
-
D.
firstAppearanceAct
Indicates the act in which an entity makes its first appearance within a work or performance.
-
E.
firstAppeared
Indicates the earliest known time or context in which an entity was introduced, observed, or came into existence.
- 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_69ca82f3b61c81908ecc2c1c96dbc2e4 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdcc8dc9c081909b6d20909ada09cf |
completed | April 2, 2026, 1:55 a.m. |
| PD | Predicate disambiguation | batch_69cd1da2cf9081908a6c0eb5247d0bc2 |
completed | April 1, 2026, 1:29 p.m. |
Created at: March 30, 2026, 8:51 p.m.