Triple
T36694174
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burlington County, New Jersey municipalities |
E906038
|
entity |
| Predicate | followLaw |
P4454
|
FINISHED |
| Object | New Jersey state law |
—
|
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: New Jersey state law | Statement: [Burlington County, New Jersey municipalities, followLaw, New Jersey state law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: followLaw Context triple: [Burlington County, New Jersey municipalities, followLaw, New Jersey state law]
-
A.
obeysLaw
chosen
Indicates that an entity follows, complies with, or acts in accordance with a specified law or set of laws.
-
B.
enforcedLaw
Indicates that an authority actively applies or upholds a specific law to regulate behavior or resolve situations.
-
C.
followsLegalAuthority
Indicates that one entity acts in accordance with, or is subordinate to, the legal power, rules, or jurisdiction exercised by another entity.
-
D.
legalAct
Indicates that an entity performs, enacts, or is involved in a formal legal action, measure, or proceeding under a legal framework.
-
E.
containsLaw
Indicates that one entity (such as a document, code, or jurisdiction) includes or encompasses a specific law within it.
- 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_69f76e70d2448190bdd3ce781ba971c5 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69ff49f888348190b9c55afa73b99e6a |
completed | May 9, 2026, 2:51 p.m. |
| PD | Predicate disambiguation | batch_69ff49614ef88190ac70b034c55ad738 |
completed | May 9, 2026, 2:49 p.m. |
Created at: May 3, 2026, 4:12 p.m.