Triple
T19943592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Write Your Own insurance companies |
E479366
|
entity |
| Predicate | relationshipToNFIP |
P137945
|
FINISHED |
| Object | servicing carrier |
—
|
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: servicing carrier | Statement: [Write Your Own insurance companies, relationshipToNFIP, servicing carrier]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToNFIP Context triple: [Write Your Own insurance companies, relationshipToNFIP, servicing carrier]
-
A.
relationshipToState
Indicates a relationship or connection that an entity has with a particular state or governmental body.
-
B.
relationshipToOASIS
Indicates the type or nature of an entity’s connection, role, or association with OASIS.
-
C.
relationToMLS
Indicates a relationship or association that an entity has with a specific MLS (Multiple Listing Service) system or record.
-
D.
relationshipToUSSF
Indicates the nature or type of connection an entity has with the United States Space Force (USSF), such as affiliation, oversight, support, or partnership.
-
E.
relationshipToAuthorities
Indicates the nature or type of connection, role, or standing that an entity has in relation to governing or official authorities.
- 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_69d8e522a17c819095165d4d24939fd8 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65a64b2788190a49c4ed40aa93b98 |
completed | April 20, 2026, 4:55 p.m. |
| PD | Predicate disambiguation | batch_69e537f47c508190853c4e009c6b5566 |
completed | April 19, 2026, 8:15 p.m. |
| PDg | Predicate description generation | batch_69e543c42c688190a22f4d31ec692377 |
completed | April 19, 2026, 9:06 p.m. |
Created at: April 10, 2026, 1:54 p.m.