Triple
T25879177
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Citeureup |
E651996
|
entity |
| Predicate | hasRegencySeatNearby |
P192034
|
FINISHED |
| Object | Cibinong |
—
|
NE NERFINISHED |
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: Cibinong | Statement: [Citeureup, hasRegencySeatNearby, Cibinong]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegencySeatNearby Context triple: [Citeureup, hasRegencySeatNearby, Cibinong]
-
A.
hasMunicipalitySeatNearby
Indicates that the municipality’s administrative seat is located in close proximity to the referenced place or entity.
-
B.
isLocatedInRegency
Indicates that one entity (typically a place or facility) is situated within the administrative area of a specific regency.
-
C.
hasParishGovernmentSeat
Indicates that a parish serves as the administrative or governmental seat for a specified jurisdiction or governing body.
-
D.
hasMunicipalLeaderSeat
Indicates that a specific location serves as the official seat or office location of a municipal leader (e.g., mayor) for a municipality.
-
E.
hasNearbyRoyalResidence
Indicates that one entity has a royal residence located in close physical proximity to it.
- 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_69e7ab3ad9d88190841ddcb93ab02e96 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69fcf36d2894819089b7db8e91b63c9d |
completed | May 7, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69fcf25c0a108190bfa823474098640b |
completed | May 7, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69fcf36bb86c8190a0a0ccf47cb56e5c |
completed | May 7, 2026, 8:17 p.m. |
Created at: April 22, 2026, 8:13 a.m.