Triple
T8448140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | And Then There Were None |
E199730
|
entity |
| Predicate | firstSerialisationYear |
P59503
|
FINISHED |
| Object | 1939 |
—
|
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: 1939 | Statement: [And Then There Were None, firstSerialisationYear, 1939]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstSerialisationYear Context triple: [And Then There Were None, firstSerialisationYear, 1939]
-
A.
firstSerializationYear
chosen
Indicates the year in which an entity (such as a work or series) was first serialized or began its initial serialized publication.
-
B.
firstSeriesYear
Indicates the year in which a series (such as a TV show, book series, or sports league season) first began or was initially released.
-
C.
firstCreationYear
Indicates the year in which something was first created or originally produced.
-
D.
firstVersionYear
Indicates the calendar year in which the first version or initial release of something was created, published, or made available.
-
E.
firstInscriptionYear
Indicates the year in which an entity was first inscribed, recorded, or officially entered into a relevant register or list.
- 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_69ca83170f9081909cd98f55614c6476 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe44480ec8190b32443a53cd4f943 |
completed | March 31, 2026, 3:12 p.m. |
| PD | Predicate disambiguation | batch_69cbd0f5a3648190beb53a139a2d5482 |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:09 p.m.