Triple

T26852699

Position	Surface form	Disambiguated ID	Type / Status
Subject	Sebring, Florida	`E676100`	entity
Predicate	racewayBuiltOn	`P162825`	FINISHED
Object	former Hendricks Army Airfield The former Hendricks Army Airfield is a decommissioned World War II-era military airfield in Sebring, Florida, that has since been repurposed for civilian uses including motorsports.	`E1743054`	NE FINISHED

How this triple was built (3 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: former Hendricks Army Airfield | Statement: [Sebring, Florida, racewayBuiltOn, former Hendricks Army Airfield]

NEDg Description generation gpt-5.1

Instruction

Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"

Input

Entity: former Hendricks Army Airfield
Triple: [Sebring, Florida, racewayBuiltOn, former Hendricks Army Airfield]

Generated description

The former Hendricks Army Airfield is a decommissioned World War II-era military airfield in Sebring, Florida, that has since been repurposed for civilian uses including motorsports.

PD Predicate disambiguation gpt-5-mini-2025-08-07

Target predicate: racewayBuiltOn
Context triple: [Sebring, Florida, racewayBuiltOn, former Hendricks Army Airfield]

A. racecourseFeature
Indicates that one entity is a physical or functional feature or component of a racecourse associated with the other entity.
B. racecourseUsed
Indicates that a particular racecourse is utilized or employed for a given event, activity, or purpose.
C. racecourseType
Indicates the specific kind or classification of a racecourse associated with an entity.
D. raceTrack
Indicates that one entity serves as a race track or racing course used by another entity for racing activities.
E. formerRacecourse
Indicates that a location previously functioned as a racecourse but no longer serves that purpose.
F. None of above. chosen

Provenance (7 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_69eee9b9d7708190a15d7485709ae981`	completed	April 27, 2026, 4:44 a.m.
NER	Named-entity recognition	`batch_69f62e4168a48190b45268f922780da6`	completed	May 2, 2026, 5:02 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a121351993481908fd6b4a0c03dcf78`	completed	May 23, 2026, 8:51 p.m.
NEDg	Description generation	`batch_6a12143774a0819094274f9c58871f16`	completed	May 23, 2026, 8:55 p.m.
NED2	Entity disambiguation (via description)	`batch_6a1214e92af48190b857bf935b0fd49d`	completed	May 23, 2026, 8:58 p.m.
PD	Predicate disambiguation	`batch_69f62c15952881908a5ea0c25904afec`	completed	May 2, 2026, 4:53 p.m.
PDg	Predicate description generation	`batch_69f62d5268ac8190835dc7119353b840`	completed	May 2, 2026, 4:58 p.m.

Created at: April 27, 2026, 5:18 a.m.