Triple

T37281303

Position	Surface form	Disambiguated ID	Type / Status
Subject	Pak Kret District	`E925400`	entity
Predicate	hasConventionCenterNearby	`P3449`	FINISHED
Object	Impact Muang Thong Thani Impact Muang Thong Thani is a major exhibition and convention center complex in the Bangkok metropolitan area, known for hosting large-scale trade shows, concerts, and international events.	`E1017566`	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: Impact Muang Thong Thani | Statement: [Pak Kret District, hasConventionCenterNearby, Impact Muang Thong Thani]

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: Impact Muang Thong Thani
Triple: [Pak Kret District, hasConventionCenterNearby, Impact Muang Thong Thani]

Generated description

Impact Muang Thong Thani is a major exhibition and convention center complex in the Bangkok metropolitan area, known for hosting large-scale trade shows, concerts, and international events.

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

Target predicate: hasConventionCenterNearby
Context triple: [Pak Kret District, hasConventionCenterNearby, Impact Muang Thong Thani]

A. isCentralVenueOf
Indicates that a venue serves as the primary or main location for a specified event, organization, or activity.
B. hasAttractionNearby chosen
Indicates that one entity is located close to another entity that serves as an attraction or point of interest.
C. hasConventionHalls
Indicates that an entity possesses or includes one or more convention halls as part of its facilities or infrastructure.
D. venueComplex
Indicates that one venue is a complex or larger facility that contains or encompasses another venue.
E. meetsNear
Indicates that two entities meet or come together at a location that is in close proximity to a specified reference point or area.
F. None of above.

Provenance (6 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_69f76eafe20c8190856d3b996a4c31a7`	completed	May 3, 2026, 3:50 p.m.
NER	Named-entity recognition	`batch_6a037c8efcd4819088c2aeead65d93df`	completed	May 12, 2026, 7:16 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a40513baeec8190941dfb7692b44c69`	completed	June 27, 2026, 10:39 p.m.
NEDg	Description generation	`batch_6a4051b5f6048190b92272bf19ee39ad`	completed	June 27, 2026, 10:41 p.m.
NED2	Entity disambiguation (via description)	`batch_6a405268e3688190b86e1ee0391e817a`	completed	June 27, 2026, 10:44 p.m.
PD	Predicate disambiguation	`batch_6a037a11efc08190bb7cacc1325b4dc6`	completed	May 12, 2026, 7:05 p.m.

Created at: May 3, 2026, 4:16 p.m.