Triple
T30712256
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Waterboys |
E781925
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Has Anybody Here Seen Hank?
"Has Anybody Here Seen Hank?" is a song by the Scottish-Irish folk rock band The Waterboys, known for its reflective lyrics and roots-influenced sound.
|
E1928165
|
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: Has Anybody Here Seen Hank? | Statement: [The Waterboys, notableWork, Has Anybody Here Seen Hank?]
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: Has Anybody Here Seen Hank? Triple: [The Waterboys, notableWork, Has Anybody Here Seen Hank?]
Generated description
"Has Anybody Here Seen Hank?" is a song by the Scottish-Irish folk rock band The Waterboys, known for its reflective lyrics and roots-influenced sound.
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_69f224acd24481908ed5f96f0d69b5dd |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f68c1fd1e081908fa0a55e82f3030b |
completed | May 2, 2026, 11:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a2899038f788190bb92d4f78ab0d41e |
completed | June 9, 2026, 10:51 p.m. |
| NEDg | Description generation | batch_6a2899f4a9488190a4ef4d96ec795595 |
completed | June 9, 2026, 10:55 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a289ac7f570819094b7940133c5ac52 |
completed | June 9, 2026, 10:59 p.m. |
Created at: April 29, 2026, 8:35 p.m.