Triple
T34511026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City of Houston municipal government |
E886019
|
entity |
| Predicate | raisesRevenueThrough |
P13615
|
FINISHED |
| Object | property taxes |
—
|
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: property taxes | Statement: [City of Houston municipal government, raisesRevenueThrough, property taxes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: raisesRevenueThrough Context triple: [City of Houston municipal government, raisesRevenueThrough, property taxes]
-
A.
revenue
Indicates the amount of income generated by an entity from its business activities or operations over a specified period.
-
B.
hasRevenueUnit
Indicates that an entity’s revenue is measured, reported, or associated in terms of a specified unit (e.g., currency or measurement unit).
-
C.
hasRevenueSystem
Indicates that one entity possesses, uses, or is associated with a particular revenue-generating system or mechanism.
-
D.
revenueSources
chosen
Indicates the relationship identifying where an entity’s revenue comes from or the different streams that generate its income.
-
E.
revenueLevel
Indicates the relative amount or tier of revenue associated with an entity or activity.
- 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_69f349ccc290819089d8e82698e53cb6 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f71fb1ab3881908e2f7c0e6f23db49 |
completed | May 3, 2026, 10:13 a.m. |
| PD | Predicate disambiguation | batch_69f71cc6397881909aaad37a9daa8a7e |
completed | May 3, 2026, 10 a.m. |
Created at: May 1, 2026, 2:01 a.m.