Triple
T14301063
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Nightmare Man |
E354562
|
entity |
| Predicate | airDateOfLastAppearance |
P69134
|
FINISHED |
| Object | 2010-10-12 |
—
|
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: 2010-10-12 | Statement: [The Nightmare Man, airDateOfLastAppearance, 2010-10-12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airDateOfLastAppearance Context triple: [The Nightmare Man, airDateOfLastAppearance, 2010-10-12]
-
A.
lastRegularAppearanceDate
Indicates the date on which an entity made its most recent standard or non-special appearance.
-
B.
lastAppearance
Indicates the most recent time or instance in which an entity appears or is present within a given context or sequence.
-
C.
thirdApparitionDate
Indicates the date on which an entity’s third apparition or appearance occurs.
-
D.
lastSeenOn
chosen
Indicates the most recent time or date at which the subject entity was observed, detected, or recorded.
-
E.
yearOfDisappearance
Indicates the specific year in which an entity disappeared or ceased to be present.
- 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_69d8278e17088190b328c5a9d4be74ff |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de717e246c819083e67ac2b3b77881 |
completed | April 14, 2026, 4:55 p.m. |
| PD | Predicate disambiguation | batch_69de2a8f81f08190af737e1654847aa6 |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:11 a.m.