Triple
T10800
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Washington Monument |
E219
|
entity |
| Predicate | hasLighting |
P1280
|
FINISHED |
| Object | exterior illumination at night |
—
|
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: exterior illumination at night | Statement: [Washington Monument, hasLighting, exterior illumination at night]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLighting Context triple: [Washington Monument, hasLighting, exterior illumination at night]
-
A.
hasPower
Indicates that one entity possesses authority, control, or influence over another entity or over a particular domain or resource.
-
B.
hasVariant
Indicates that one entity exists as an alternative form, version, or variation of another entity.
-
C.
hasPart
Indicates that one entity is a component, segment, or constituent part of another entity.
-
D.
hasLimitation
Indicates that an entity is subject to a constraint, restriction, or boundary that limits its scope, capability, or applicability.
-
E.
envisionedAs
Indicates that one entity is mentally pictured, imagined, or conceived in terms of another entity or role.
- 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_69a23d7ad88c8190bffe8ab091d86642 |
completed | Feb. 28, 2026, 12:57 a.m. |
| NER | Named-entity recognition | batch_69a242cd8fb481909562f114f4ce7700 |
completed | Feb. 28, 2026, 1:20 a.m. |
| PD | Predicate disambiguation | batch_69a23fe6b0bc8190bcce9b74f2c5fb08 |
completed | Feb. 28, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69a242cce40481908e5eae0c94313c25 |
completed | Feb. 28, 2026, 1:20 a.m. |
Created at: Feb. 28, 2026, 1:02 a.m.