Triple
T32555936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cupid (2009 TV series) |
E832095
|
entity |
| Predicate | hasFictionalUniverseElement |
P15645
|
FINISHED |
| Object |
Roman god Cupid
The Roman god Cupid is the mythological deity of love and desire, traditionally depicted as a winged youth whose arrows cause people to fall in love.
|
E2013046
|
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: Roman god Cupid | Statement: [Cupid (2009 TV series), hasFictionalUniverseElement, Roman god Cupid]
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: Roman god Cupid Triple: [Cupid (2009 TV series), hasFictionalUniverseElement, Roman god Cupid]
Generated description
The Roman god Cupid is the mythological deity of love and desire, traditionally depicted as a winged youth whose arrows cause people to fall in love.
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_69f34926b9848190ace47d2dd0a0de7c |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c5fbbd308190b7af8be4c25e6ff1 |
completed | May 3, 2026, 3:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a347b901f64819090878c5d44152293 |
completed | June 18, 2026, 11:13 p.m. |
| NEDg | Description generation | batch_6a347c427de8819083c0a683e40f660b |
completed | June 18, 2026, 11:16 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a347e0a2ed48190b8648eb4406bef26 |
completed | June 18, 2026, 11:23 p.m. |
Created at: May 1, 2026, 1:03 a.m.