Triple

T24118055

Position	Surface form	Disambiguated ID	Type / Status
Subject	John May	`E597573`	entity
Predicate	locatedInWorkplace	`P146199`	FINISHED
Object	Chicago garage Chicago garage was a Chicago-based automobile garage notorious as the site of the 1929 Saint Valentine’s Day Massacre involving gangster John May.	`E1617508`	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: Chicago garage | Statement: [John May, locatedInWorkplace, Chicago garage]

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: Chicago garage
Triple: [John May, locatedInWorkplace, Chicago garage]

Generated description

Chicago garage was a Chicago-based automobile garage notorious as the site of the 1929 Saint Valentine’s Day Massacre involving gangster John May.

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

Target predicate: locatedInWorkplace
Context triple: [John May, locatedInWorkplace, Chicago garage]

A. locationInWork
Indicates that one entity specifies the place or setting where another entity occurs, is situated, or takes place within a particular work (e.g., a scene’s location in a film or a chapter’s setting in a book).
B. residesInWork
Indicates that a person or entity lives or is based within the location, setting, or environment defined by a particular work (such as a book, film, or other creative piece).
C. placeInWork
Indicates that one entity is located or occurs within the spatial or structural context of another entity in a work.
D. appliedToWorkCurrentLocation
Indicates that an application was submitted for a job or position at the entity’s current work location.
E. associatedWithWorkplace chosen
Indicates a relationship where an entity has a connection or affiliation with a particular workplace or place of employment.
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_69e288c74200819098ab875b592cb39f`	completed	April 17, 2026, 7:23 p.m.
NER	Named-entity recognition	`batch_69f1dee091c48190a55d36f28c332749`	completed	April 29, 2026, 10:35 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a0f968e05e88190b9579b5c25d7a09c`	completed	May 21, 2026, 11:34 p.m.
NEDg	Description generation	`batch_6a0f982bbdf881909c1651b1d2a91c85`	completed	May 21, 2026, 11:41 p.m.
NED2	Entity disambiguation (via description)	`batch_6a0f99ae95f88190b09d6ad00f85290d`	completed	May 21, 2026, 11:47 p.m.
PD	Predicate disambiguation	`batch_69f17651458c8190bbfd301883e46085`	completed	April 29, 2026, 3:09 a.m.

Created at: April 17, 2026, 11:05 p.m.