Triple
T8098988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trenton Makes Bridge |
E189057
|
entity |
| Predicate | illumination |
P73043
|
FINISHED |
| Object | neon lighting |
—
|
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: neon lighting | Statement: [Trenton Makes Bridge, illumination, neon lighting]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: illumination Context triple: [Trenton Makes Bridge, illumination, neon lighting]
-
A.
illuminationCondition
Indicates the lighting or brightness conditions under which an event, observation, or interaction takes place.
-
B.
originalIllumination
Indicates that an entity provides the initial or primary source of light or illumination for another entity or context.
-
C.
lightType
chosen
Indicates the specific category or kind of light associated with an entity or lighting setup.
-
D.
litOn
Indicates that one entity is illuminated or activated by a light source associated with another entity.
-
E.
lightingCharacteristic
Indicates the specific qualities or properties of how something is lit, such as brightness, color, direction, or style of illumination.
- 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_69ca82b886d88190a9cba0d5a4a27521 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb42961ad4819085d023427fc5ac5f |
completed | March 31, 2026, 3:42 a.m. |
| PD | Predicate disambiguation | batch_69cb04a14cd88190a79ed26cbeec1c33 |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:30 p.m.