Triple
T9938783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lebanon, Pennsylvania |
E194023
|
entity |
| Predicate | roleInCounty |
P82325
|
FINISHED |
| Object | administrative center of Lebanon County |
—
|
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: administrative center of Lebanon County | Statement: [Lebanon, Pennsylvania, roleInCounty, administrative center of Lebanon County]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInCounty Context triple: [Lebanon, Pennsylvania, roleInCounty, administrative center of Lebanon County]
-
A.
inCounty
Indicates that one entity is geographically or administratively located within the boundaries of a specified county.
-
B.
countyFunction
chosen
Indicates that a county serves a particular administrative or governmental role or performs a specified function.
-
C.
homeCounty
Indicates that a specified county is the primary home or place of residence for a given person or entity.
-
D.
isSubjectToCountyGovernment
Indicates that an entity falls under the jurisdiction, authority, or administrative control of a county-level government.
-
E.
isInCountySeatOf
Indicates that one entity is located within the town or city that serves as the administrative center (county seat) of a specified county.
- 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_69ca82e409348190a393777356b80a2a |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb5e64760819094f599f158d32f33 |
completed | April 2, 2026, 12:18 a.m. |
| PD | Predicate disambiguation | batch_69cd1d9428cc81909b4b4938566d78a7 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:44 p.m.