Triple
T341751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | International Standard Book Number |
E6851
|
entity |
| Predicate | 10DigitInUseFrom |
P12039
|
FINISHED |
| Object | 1970 |
—
|
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: 1970 | Statement: [International Standard Book Number, 10DigitInUseFrom, 1970]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 10DigitInUseFrom Context triple: [International Standard Book Number, 10DigitInUseFrom, 1970]
-
A.
hasAreaCode
Indicates that a specified telephone area code is assigned to or associated with a particular geographic region, location, or phone service entity.
-
B.
associatedNumber
Indicates a relationship where a specific number is linked or assigned to an entity as its associated value.
-
C.
nameUsedBy
Indicates that a particular name is employed or referenced by a specific entity.
-
D.
callingCode
Indicates the telephone country or area code associated with an entity for making phone calls.
-
E.
areaCode
Indicates that a location, phone number, or region is associated with a specific telephone area code.
- F. None of above. chosen
Provenance (4 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_69a2e7951ba08190960e90823b5078f3 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eae611f88190955fbebe2b01835b |
completed | Feb. 28, 2026, 1:17 p.m. |
| PD | Predicate disambiguation | batch_69a2e95197fc8190820e8ebd0d7d27fa |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea0a4c448190a8a179daa9b90645 |
completed | Feb. 28, 2026, 1:13 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.