Triple
T15678758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martha Coleman |
E377515
|
entity |
| Predicate | knownFor |
P22
|
FINISHED |
| Object | Praise |
E77894
|
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: Praise | Statement: [Martha Coleman, knownFor, Praise]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Praise Context triple: [Martha Coleman, knownFor, Praise]
-
A.
Praise
chosen
Praise is a 1998 Australian film directed by John Curran, adapted from Andrew McGahan’s novel, that explores a raw, intimate relationship between two misfit lovers.
-
B.
Laud
Laud is a notable English surname most famously borne by William Laud, the 17th-century Archbishop of Canterbury under King Charles I.
-
C.
Acclaim
Acclaim is a virtual reality product or platform associated with the VR Commodore system.
-
D.
Put a Praise on It
"Put a Praise on It" is a popular contemporary gospel worship song by Tasha Cobbs known for its powerful vocals and celebratory message of praise.
-
E.
fountain of praise
The Fountain of Praise is a sculptural water feature at Thanks-Giving Square in Dallas, Texas, symbolizing gratitude and spiritual reflection within the urban park.
- 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_69d85cd2e28481909d4e975bee20872f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04f2f1640819086efd5a73bb9734a |
completed | April 16, 2026, 2:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff6ee0446881909e9c2504d51d49a3 |
completed | May 9, 2026, 5:29 p.m. |
Created at: April 10, 2026, 4:16 a.m.