Triple
T4238
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University City, Philadelphia |
E81
|
entity |
| Predicate | postalCodeRegion |
P222
|
FINISHED |
| Object | 19104 |
—
|
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: 19104 | Statement: [University City, Philadelphia, postalCodeRegion, 19104]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: postalCodeRegion Context triple: [University City, Philadelphia, postalCodeRegion, 19104]
-
A.
postalCode
chosen
Indicates the numerical or alphanumerical code assigned to a geographic area for mail delivery associated with an entity.
-
B.
hasRegion
Indicates that an entity includes, contains, or is associated with a specific geographic or administrative region as part of its scope or structure.
-
C.
areaCode
Indicates that a location, phone number, or region is associated with a specific telephone area code.
-
D.
FIPSCode
Indicates the standardized Federal Information Processing Standards (FIPS) code assigned to identify a specific geographic or administrative entity.
-
E.
hasAreaCode
Indicates that a specified telephone area code is assigned to or associated with a particular geographic region, location, or phone service 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_69a238d6b47881909e68288aed2fd858 |
completed | Feb. 28, 2026, 12:37 a.m. |
| NER | Named-entity recognition | batch_69a23c24b3d08190a714126292fd5479 |
completed | Feb. 28, 2026, 12:51 a.m. |
| PD | Predicate disambiguation | batch_69a23998af288190855f0456740cbd51 |
completed | Feb. 28, 2026, 12:40 a.m. |
Created at: Feb. 28, 2026, 12:40 a.m.