Triple

T30745299

Position	Surface form	Disambiguated ID	Type / Status
Subject	Bábí movement	`E782800`	entity
Predicate	hadArmedConflictsAt	`P13112`	FINISHED
Object	Shaykh Tabarsí Shaykh Tabarsí was the site of a pivotal 19th-century Bábí stronghold and siege in Iran, where early followers of the Báb mounted a historic armed resistance against Qajar forces.	`E1935427`	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: Shaykh Tabarsí | Statement: [Bábí movement, hadArmedConflictsAt, Shaykh Tabarsí]

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: Shaykh Tabarsí
Triple: [Bábí movement, hadArmedConflictsAt, Shaykh Tabarsí]

Generated description

Shaykh Tabarsí was the site of a pivotal 19th-century Bábí stronghold and siege in Iran, where early followers of the Báb mounted a historic armed resistance against Qajar forces.

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

Target predicate: hadArmedConflictsAt
Context triple: [Bábí movement, hadArmedConflictsAt, Shaykh Tabarsí]

A. hasHistoricalPeriodOfConflict
Indicates that there exists a specific historical period during which the related entities were engaged in conflict or hostilities.
B. militaryConflictIn
Indicates that a military conflict takes place within, or is geographically located in, a specified area or region.
C. warParticipatedIn chosen
Indicates that an entity took part as a combatant or active participant in a specific war or armed conflict.
D. conflictExperience
Indicates that an entity has undergone or been involved in a conflict, such as a dispute, struggle, or confrontation.
E. militaryConflict
Indicates a relationship where two or more parties are engaged in organized, armed hostilities or warfare against each other.
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_69f224aeb1588190897d395e8ed2acb8`	completed	April 29, 2026, 3:33 p.m.
NER	Named-entity recognition	`batch_69f68f6cba0c8190a02288899be05007`	completed	May 2, 2026, 11:57 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a28c7bbc6408190971b850dd79ca7c6`	completed	June 10, 2026, 2:11 a.m.
NEDg	Description generation	`batch_6a28cd15b8908190b09a385ba653edfc`	completed	June 10, 2026, 2:33 a.m.
NED2	Entity disambiguation (via description)	`batch_6a28cd6db5a48190a732e01a102bca13`	completed	June 10, 2026, 2:35 a.m.
PD	Predicate disambiguation	`batch_69f686140aa08190a35f62572b2db9b6`	completed	May 2, 2026, 11:17 p.m.

Created at: April 29, 2026, 8:38 p.m.