Triple
T9846400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | My Night at Maud’s |
E239351
|
entity |
| Predicate | seriesOrdinalInSixMoralTales |
P50204
|
FINISHED |
| Object | third |
—
|
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: third | Statement: [My Night at Maud’s, seriesOrdinalInSixMoralTales, third]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seriesOrdinalInSixMoralTales Context triple: [My Night at Maud’s, seriesOrdinalInSixMoralTales, third]
-
A.
moralOfMyth
Indicates the underlying lesson, ethical teaching, or message conveyed by a myth.
-
B.
storyNumber
chosen
Indicates the numerical identifier assigned to a specific story within a collection, sequence, or dataset.
-
C.
talesCount
Indicates the number of tales associated with or attributed to a given entity.
-
D.
narrativeSequence
Indicates that one event or narrative element follows another in a temporal or logical storytelling order.
-
E.
seriesOf
Indicates that one entity is a sequence or ordered set of related items, events, or parts that collectively form or belong to another entity.
- 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_69ca84e3f0c48190ada72a65ebd50efd |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb36156308190b26892702f3b41e0 |
completed | April 2, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69cd03e57cac8190914bb5ae608a6e0e |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:34 p.m.