Triple
T27261073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pennsylvania 6-5000 |
E687763
|
entity |
| Predicate | telephoneNumberInTitle |
P162287
|
FINISHED |
| Object | Pennsylvania 6-5000 |
—
|
NE NERFINISHED |
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: Pennsylvania 6-5000 | Statement: [Pennsylvania 6-5000, telephoneNumberInTitle, Pennsylvania 6-5000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: telephoneNumberInTitle Context triple: [Pennsylvania 6-5000, telephoneNumberInTitle, Pennsylvania 6-5000]
-
A.
titleNumber
Indicates the numerical designation or sequence number assigned to a title within an ordered set of titles.
-
B.
commonTitle
Indicates that two or more entities share the same title or designation.
-
C.
usesTitle
Indicates that one entity refers to or addresses another entity using a specific title or formal designation.
-
D.
usesTitleIn
Indicates that an entity is referred to using a particular title within a specified context or medium.
-
E.
titleHolderName
Indicates the name of the person or entity that holds a particular title or position.
- 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_69ef3557abc481908bf3c146f0f3356a |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69f626ee531c81908f23232136023c66 |
completed | May 2, 2026, 4:31 p.m. |
| PD | Predicate disambiguation | batch_69f620e38aec8190bb184edcdbd6da64 |
completed | May 2, 2026, 4:05 p.m. |
| PDg | Predicate description generation | batch_69f622a8fe7c819096e8a43db263a423 |
completed | May 2, 2026, 4:13 p.m. |
Created at: April 27, 2026, 10:52 a.m.