Triple
T25008790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flesh of My Flesh, Blood of My Blood |
E625925
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object |
Waah Dean
Waah Dean is a music industry executive and producer best known for his work overseeing major hip-hop projects, including albums by DMX.
|
E587642
|
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: Waah Dean | Statement: [Flesh of My Flesh, Blood of My Blood, executiveProducer, Waah Dean]
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: Waah Dean Triple: [Flesh of My Flesh, Blood of My Blood, executiveProducer, Waah Dean]
Generated description
Waah Dean is a music industry executive and producer best known for his work overseeing major hip-hop projects, including albums by DMX.
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_69e2ff27755881908490178e83701160 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f44b13897881909482f296204b8355 |
completed | May 1, 2026, 6:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a1048ae0ae08190b088fe193cbf9788 |
completed | May 22, 2026, 12:14 p.m. |
| NEDg | Description generation | batch_6a104a450fe08190bb6f266341f1f595 |
completed | May 22, 2026, 12:21 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a104bc667e48190bb0feadc5b324cde |
completed | May 22, 2026, 12:27 p.m. |
Created at: April 18, 2026, 6:05 a.m.