Triple

T28144071
Position Surface form Disambiguated ID Type / Status
Subject Temple of the Forbidden Eye E714426 entity
Predicate hasGuardian P28704 FINISHED
Object Mara
Mara is the powerful, idolized deity who serves as the central supernatural antagonist and guardian spirit within the Indiana Jones Adventure: Temple of the Forbidden Eye attraction at Disneyland.
E1593763 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: Mara | Statement: [Temple of the Forbidden Eye, hasGuardian, Mara]
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: Mara
Triple: [Temple of the Forbidden Eye, hasGuardian, Mara]
Generated description
Mara is the powerful, idolized deity who serves as the central supernatural antagonist and guardian spirit within the Indiana Jones Adventure: Temple of the Forbidden Eye attraction at Disneyland.

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_69efd6b033208190bf74f80a147e2092 completed April 27, 2026, 9:35 p.m.
NER Named-entity recognition batch_69f6417088ac81909668030d2a9daebc completed May 2, 2026, 6:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1606feddfc8190bc3da245b72ae77b completed May 26, 2026, 8:47 p.m.
NEDg Description generation batch_6a160d0b43ec819083ac78ba71ef05ab completed May 26, 2026, 9:13 p.m.
NED2 Entity disambiguation (via description) batch_6a160d68c9f88190bc222a50ba6790a4 completed May 26, 2026, 9:15 p.m.
Created at: April 27, 2026, 9:55 p.m.