Triple

T34691660

Position	Surface form	Disambiguated ID	Type / Status
Subject	Ellis Unit	`E890913`	entity
Predicate	deathRowRelocatedTo	`P182290`	FINISHED
Object	Allan B. Polunsky Unit The Allan B. Polunsky Unit is a Texas state prison best known for housing the state’s male death row inmates under high-security conditions.	`E2108045`	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: Allan B. Polunsky Unit | Statement: [Ellis Unit, deathRowRelocatedTo, Allan B. Polunsky Unit]

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: Allan B. Polunsky Unit
Triple: [Ellis Unit, deathRowRelocatedTo, Allan B. Polunsky Unit]

Generated description

The Allan B. Polunsky Unit is a Texas state prison best known for housing the state’s male death row inmates under high-security conditions.

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

Target predicate: deathRowRelocatedTo
Context triple: [Ellis Unit, deathRowRelocatedTo, Allan B. Polunsky Unit]

A. deathRowIncarceration
Indicates that an individual is incarcerated in prison under a death sentence, awaiting execution.
B. deathPeninsula
Indicates a relationship where a death occurs on, near, or in association with a specific peninsula.
C. deathPenaltyImposed
Indicates that a legal authority has formally assigned the death penalty as the punishment for an entity.
D. diedInCustodyOf
Indicates that an individual died while under the control, supervision, or physical custody of a specified authority or entity.
E. deathPenaltyImposedFor
Indicates that a death penalty has been officially assigned as the punishment for a particular offense or action.
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_69f349db7ab8819086808e833f472871`	completed	April 30, 2026, 12:23 p.m.
NER	Named-entity recognition	`batch_69f7886be6d8819095ec62e4f2cee858`	completed	May 3, 2026, 5:39 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a3752fae58c8190a918bc66c445b98d`	completed	June 21, 2026, 2:56 a.m.
NEDg	Description generation	`batch_6a37538a0d948190949592c8f833958c`	completed	June 21, 2026, 2:59 a.m.
NED2	Entity disambiguation (via description)	`batch_6a37541fa8d48190aef474f094893f32`	completed	June 21, 2026, 3:01 a.m.
PD	Predicate disambiguation	`batch_69f7841440f48190b4346c08855951d2`	completed	May 3, 2026, 5:21 p.m.
PDg	Predicate description generation	`batch_69f7886b27f08190ab4580f949222c93`	completed	May 3, 2026, 5:39 p.m.

Created at: May 1, 2026, 2:05 a.m.