Triple
T1097415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Social Security number |
E24300
|
entity |
| Predicate | numericFormat |
P5329
|
FINISHED |
| Object | XXX-XX-XXXX |
—
|
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: XXX-XX-XXXX | Statement: [Social Security number, numericFormat, XXX-XX-XXXX]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numericFormat Context triple: [Social Security number, numericFormat, XXX-XX-XXXX]
-
A.
currencyNumber
Indicates the numerical value or denomination associated with a specific currency.
-
B.
currencyAppearance
Indicates how a currency physically looks or is visually represented, such as its design, color, or format.
-
C.
notationSystem
Indicates a relationship where one entity is the system or method of notation used to represent or encode another entity.
-
D.
decimalized
Indicates that something has been converted into or expressed in decimal form, typically changing from another numeral or measurement system to a base-10 representation.
-
E.
notationPattern
chosen
Indicates a recurring way in which something is symbolically represented or written, such as a consistent style or structure of notation used for an entity or concept.
- 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_69a4940542308190ac2a0b1f730b7cfc |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b9a1d3108190b2a304fef429848d |
completed | March 1, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69a4b745ef3481909a7ce4647c8567b3 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.