Triple
T155993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magdalena Contreras |
E3182
|
entity |
| Predicate | hasTelephoneAreaCode |
P223
|
FINISHED |
| Object | 55 |
—
|
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: 55 | Statement: [Magdalena Contreras, hasTelephoneAreaCode, 55]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTelephoneAreaCode Context triple: [Magdalena Contreras, hasTelephoneAreaCode, 55]
-
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.
areaCode
chosen
Indicates that a location, phone number, or region is associated with a specific telephone area code.
-
C.
callingCode
Indicates the telephone country or area code associated with an entity for making phone calls.
-
D.
postalArea
Indicates that one entity is the postal or ZIP code area associated with the location or address represented by the other entity.
-
E.
hasPostalCodePrefix
Indicates that a location’s postal code begins with a specified sequence of characters.
- 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_69a2527757ec819090b8becb2cf1a862 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a258808ff08190a06b6206f635612b |
completed | Feb. 28, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69a2565ded588190a27319aaa0130b4f |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.