Triple
T678506
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George M. Steinbrenner Field |
E13129
|
entity |
| Predicate | hasLights |
P1280
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [George M. Steinbrenner Field, hasLights, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLights Context triple: [George M. Steinbrenner Field, hasLights, yes]
-
A.
hasLighting
chosen
Indicates that one entity is equipped with, contains, or is characterized by a particular type or configuration of lighting.
-
B.
hasRunwayLighting
Indicates that a runway is equipped with lighting systems to aid visibility and operations, typically during low-light or night conditions.
-
C.
led
Indicates that one entity guided, directed, or was in charge of another entity or activity, typically over a period of time.
-
D.
hasTorchRelay
Indicates that an event or entity includes or is associated with a torch relay as part of its activities or proceedings.
-
E.
lanternColor
Indicates that one entity specifies or describes the color attribute of a lantern associated with another entity.
- 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_69a4933d3bf88190972041cd8cf143b9 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a04e17088190943d54977eb3f83a |
completed | March 1, 2026, 8:23 p.m. |
| PD | Predicate disambiguation | batch_69a49d1d79608190a849ba9ffad2879d |
completed | March 1, 2026, 8:10 p.m. |
Created at: March 1, 2026, 7:36 p.m.