Triple
T8129331
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Kingdom |
E189815
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object |
Forward Pass
Forward Pass is a film and television production company best known for producing Terrence Malick’s historical drama "The New World."
|
E714738
|
NE FINISHED |
How this triple was built (4 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: Forward Pass | Statement: [The Kingdom, productionCompany, Forward Pass]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Forward Pass Context triple: [The Kingdom, productionCompany, Forward Pass]
-
A.
Forward
Forward is the state motto of Wisconsin, expressing its emphasis on progress and continual improvement.
-
B.
Forward
Forward was the central campaign slogan used by Barack Obama during his 2012 U.S. presidential re-election bid, emphasizing progress and continuation of his policies.
-
C.
Forward Movement
Forward Movement is a film and television production company known for developing and producing screen content.
-
D.
Forward!
Forward! is the English title of the 1972 Italian political drama film "Avanti!".
-
E.
Ready and Forward
Ready and Forward is the official motto of the 10th U.S. Cavalry Regiment, reflecting its historic reputation for preparedness and aggressive action.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Forward Pass Triple: [The Kingdom, productionCompany, Forward Pass]
Generated description
Forward Pass is a film and television production company best known for producing Terrence Malick’s historical drama "The New World."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Forward Pass Target entity description: Forward Pass is a film and television production company best known for producing Terrence Malick’s historical drama "The New World."
-
A.
Forward
Forward is the state motto of Wisconsin, expressing its emphasis on progress and continual improvement.
-
B.
Forward
Forward was the central campaign slogan used by Barack Obama during his 2012 U.S. presidential re-election bid, emphasizing progress and continuation of his policies.
-
C.
Forward Movement
Forward Movement is a film and television production company known for developing and producing screen content.
-
D.
Forward!
Forward! is the English title of the 1972 Italian political drama film "Avanti!".
-
E.
Ready and Forward
Ready and Forward is the official motto of the 10th U.S. Cavalry Regiment, reflecting its historic reputation for preparedness and aggressive action.
- F. None of above. chosen
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_69ca82bcb4848190a9a9d036ad768642 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb43b6b4dc8190be237e6dd21c863b |
completed | March 31, 2026, 3:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc947303f881908e16af664fb74dc8 |
completed | April 1, 2026, 3:43 a.m. |
| NEDg | Description generation | batch_69cca83322748190bdd532552d972089 |
completed | April 1, 2026, 5:08 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cca913304c8190a0ce9c468d98269f |
completed | April 1, 2026, 5:11 a.m. |
Created at: March 30, 2026, 5:34 p.m.