Triple

T32904913
Position Surface form Disambiguated ID Type / Status
Subject International Horror Guild Award E841708 entity
Predicate notableRecipient P108 FINISHED
Object Caitlín R. Kiernan
Caitlín R. Kiernan is an Irish-born American author acclaimed for her dark fantasy and horror fiction, noted for her atmospheric prose and psychologically complex narratives.
E2029611 NE FINISHED

How this triple was built (2 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: Caitlín R. Kiernan | Statement: [International Horror Guild Award, notableRecipient, Caitlín R. Kiernan]
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: Caitlín R. Kiernan
Triple: [International Horror Guild Award, notableRecipient, Caitlín R. Kiernan]
Generated description
Caitlín R. Kiernan is an Irish-born American author acclaimed for her dark fantasy and horror fiction, noted for her atmospheric prose and psychologically complex narratives.

Provenance (5 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_69f34946a5208190bbd79f0fec4323bd completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d07d5f148190a88573b65626b5e1 completed May 3, 2026, 4:35 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34d25b36848190b43cf52355a8913c completed June 19, 2026, 5:23 a.m.
NEDg Description generation batch_6a34d32a229481909a407bea93892806 completed June 19, 2026, 5:27 a.m.
NED2 Entity disambiguation (via description) batch_6a34d3ab5e98819091f34300bf83621d completed June 19, 2026, 5:29 a.m.
Created at: May 1, 2026, 1:19 a.m.