Triple
T11288688
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | De Marne |
E267264
|
entity |
| Predicate | hadPostalCodePrefix |
P961
|
FINISHED |
| Object | 9960–9979 (approximate range) |
—
|
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: 9960–9979 (approximate range) | Statement: [De Marne, hadPostalCodePrefix, 9960–9979 (approximate range)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadPostalCodePrefix Context triple: [De Marne, hadPostalCodePrefix, 9960–9979 (approximate range)]
-
A.
hasPostalCodePrefix
chosen
Indicates that a location’s postal code begins with a specified sequence of characters.
-
B.
postalCode
Indicates the numerical or alphanumerical code assigned to a geographic area for mail delivery associated with an entity.
-
C.
postalArea
Indicates that one entity is the postal or ZIP code area associated with the location or address represented by the other entity.
-
D.
hasPostalFeature
Indicates that one entity possesses, includes, or is characterized by a specific postal-related feature (such as a code, service, or facility).
-
E.
hasPostalAssociationWith
Indicates a relationship in which one entity is connected to another through postal services, such as mail handling, delivery, routing, or shared postal operations.
- 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_69d6aac993a08190a6f36445ebaf9a43 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e98875a08190b8509fe55e49d52d |
completed | April 9, 2026, 6:01 p.m. |
| PD | Predicate disambiguation | batch_69d787a240588190aa097298f951c915 |
completed | April 9, 2026, 11:04 a.m. |
Created at: April 8, 2026, 9:32 p.m.