Triple
T4047012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Melody Time |
E84089
|
entity |
| Predicate | segment |
P889
|
FINISHED |
| Object | Trees |
E306556
|
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: Trees | Statement: [Melody Time, segment, Trees]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Trees Context triple: [Melody Time, segment, Trees]
-
A.
Trees
chosen
Trees is a well-known live music venue in Dallas, Texas, recognized for hosting a wide range of rock, metal, and alternative acts in an intimate club setting.
-
B.
Trees Lounge
Trees Lounge is a 1996 independent drama film written, directed by, and starring Steve Buscemi, focusing on a down-and-out mechanic who spends his days drinking in a neighborhood bar.
-
C.
Bo tree
The Bo tree is the sacred fig tree under which Siddhartha Gautama is believed to have attained enlightenment, making it a central symbol in Buddhism.
-
D.
Tanne
Tanne is a small village in the Harz region of central Germany, now part of the town of Oberharz am Brocken.
-
E.
Woods
Woods is a common English surname of Anglo-Saxon origin, typically referring to someone who lived or worked in or near a forest.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69aed930bd5c819083e7dcc14fc44f69 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb62593c8190ab8462c4d9cd9d08 |
completed | March 9, 2026, 4:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5565466648190802a9b8fd88c3572 |
completed | March 14, 2026, 12:36 p.m. |
Created at: March 9, 2026, 3:37 p.m.