Triple
T28434139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Almighty So |
E715215
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object |
Woulda Coulda
"Woulda Coulda" is a track by Chicago rapper Chief Keef from his 2013 mixtape *Almighty So*, showcasing his signature drill sound and ad-lib-heavy delivery.
|
E1817681
|
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: Woulda Coulda | Statement: [Almighty So, hasTrack, Woulda Coulda]
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: Woulda Coulda Triple: [Almighty So, hasTrack, Woulda Coulda]
Generated description
"Woulda Coulda" is a track by Chicago rapper Chief Keef from his 2013 mixtape *Almighty So*, showcasing his signature drill sound and ad-lib-heavy delivery.
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_69efd6b253888190b3c7222ed6a403a8 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f64e37f7fc819083809149b6661e3c |
completed | May 2, 2026, 7:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a16332921608190bcabc427d094b9f8 |
completed | May 26, 2026, 11:56 p.m. |
| NEDg | Description generation | batch_6a163560594081908c70213f08ef3f83 |
completed | May 27, 2026, 12:05 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a1639a6eae881909596f0e21af432a5 |
completed | May 27, 2026, 12:24 a.m. |
Created at: April 28, 2026, 1:41 a.m.