Triple

T37103480

Position	Surface form	Disambiguated ID	Type / Status
Subject	Chandikeswarar	`E918772`	entity
Predicate	languageName_ta	`P33804`	FINISHED
Object	சண்டிகேசுவரர் சண்டிகேசுவரர் என்பது சிவபெருமானின் பரம பக்தராகவும் கோயில்களில் தனி சன்னதி பெற்ற காவல் தெய்வமாகவும் வணங்கப்படும் முக்கிய சைவ நாயன்மார்களில் ஒருவராகும்.	`E2212460`	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: சண்டிகேசுவரர் | Statement: [Chandikeswarar, languageName_ta, சண்டிகேசுவரர்]

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: சண்டிகேசுவரர்
Triple: [Chandikeswarar, languageName_ta, சண்டிகேசுவரர்]

Generated description

சண்டிகேசுவரர் என்பது சிவபெருமானின் பரம பக்தராகவும் கோயில்களில் தனி சன்னதி பெற்ற காவல் தெய்வமாகவும் வணங்கப்படும் முக்கிய சைவ நாயன்மார்களில் ஒருவராகும்.

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

Target predicate: languageName_ta
Context triple: [Chandikeswarar, languageName_ta, சண்டிகேசுவரர்]

A. nameInTamil chosen
Indicates that an entity’s name is expressed or written in the Tamil language.
B. titleInTamilScript
Indicates that the title of an entity is expressed or recorded in the Tamil script.
C. languageName
Indicates the specific name assigned to a language in the relationship.
D. languageNameTurkish
Indicates that the associated language’s name is given in Turkish.
E. monthInTamilCalendar
Indicates that one entity is a specific month as defined in the Tamil calendar system.
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_69f76e9b99c8819096164b21ff5bd996`	completed	May 3, 2026, 3:49 p.m.
NER	Named-entity recognition	`batch_6a016cc5abcc8190b64094c777b40f6f`	completed	May 11, 2026, 5:44 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a3efdd7df748190b71cb85588a1774e`	completed	June 26, 2026, 10:31 p.m.
NEDg	Description generation	`batch_6a3eff236cfc8190860fe9c296aa5fd2`	completed	June 26, 2026, 10:37 p.m.
NED2	Entity disambiguation (via description)	`batch_6a3f0a529f148190b754be085e044efd`	completed	June 26, 2026, 11:25 p.m.
PD	Predicate disambiguation	`batch_6a016b997ecc8190818207c57b9cbf17`	completed	May 11, 2026, 5:39 a.m.

Created at: May 3, 2026, 4:14 p.m.