Triple
T23825720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Neon (live version) |
E589366
|
entity |
| Predicate | includedIn |
P1393
|
FINISHED |
| Object |
Any Given Thursday
Any Given Thursday is a live album and concert film by John Mayer, capturing his early 2000s performance and showcasing live versions of his popular songs.
|
E1603014
|
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: Any Given Thursday | Statement: [Neon (live version), includedIn, Any Given Thursday]
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: Any Given Thursday Triple: [Neon (live version), includedIn, Any Given Thursday]
Generated description
Any Given Thursday is a live album and concert film by John Mayer, capturing his early 2000s performance and showcasing live versions of his popular songs.
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_69e25d1922d481909cab567c06a802ab |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c7f114cc8190a8a557b7fd12c5c6 |
completed | April 29, 2026, 8:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0f699ab3548190ab4928e97fabe104 |
completed | May 21, 2026, 8:22 p.m. |
| NEDg | Description generation | batch_6a0f6a2b96048190b3f1e6465232f4ba |
completed | May 21, 2026, 8:25 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0f6d4eddf0819081caec7518121664 |
completed | May 21, 2026, 8:38 p.m. |
Created at: April 17, 2026, 8 p.m.