Triple
T7235256
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laurelwood |
E155205
|
entity |
| Predicate | geographicRegionType |
P54124
|
FINISHED |
| Object | tract |
—
|
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: tract | Statement: [Laurelwood, geographicRegionType, tract]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: geographicRegionType Context triple: [Laurelwood, geographicRegionType, tract]
-
A.
geographicalRegionType
chosen
Indicates the specific kind or category of geographical region that an entity belongs to (e.g., continent, country, province, or city).
-
B.
countryRegion
Indicates that a country is located within, or belongs to, a specific geographic or administrative region.
-
C.
populationRegionType
Indicates the type or category of region (e.g., city, state, country) to which a given population value or statistic applies.
-
D.
politicalRegionType
Indicates the classification of a political region according to its governmental or administrative type (e.g., state, province, municipality).
-
E.
placeRegion
Indicates that a place is located within, or is part of, a larger geographic or administrative region.
- 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_69c688143bfc81908d4176617735e601 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ea552a688190a00f5d0ad982f787 |
completed | March 27, 2026, 8:36 p.m. |
| PD | Predicate disambiguation | batch_69c6e7644648819096a5e2de5d0dbe97 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 2:55 p.m.