Triple
T10210452
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Space (novel) |
E242311
|
entity |
| Predicate | hasFictionalCharacter |
P15645
|
FINISHED |
| Object |
Norman Grant
Norman Grant is a fictional character from the science fiction novel "Space" by James A. Michener.
|
E850364
|
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: Norman Grant | Statement: [Space (novel), hasFictionalCharacter, Norman Grant]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Norman Grant Context triple: [Space (novel), hasFictionalCharacter, Norman Grant]
-
A.
Norman Clyde
Norman Clyde was a renowned American mountaineer and climber famed for his prolific first ascents and exploration of the Sierra Nevada.
-
B.
Norman Riley
Norman Riley is a distinguished mathematician and fluid dynamicist recognized for his influential contributions to theoretical and applied fluid mechanics.
-
C.
Norman Ferguson
Norman Ferguson was an American animator and film director at Walt Disney Studios, best known for his influential work on classic Disney features during the Golden Age of animation.
-
D.
Norman Harris
Norman Harris was an American soul and disco guitarist, songwriter, and producer closely associated with the Philadelphia soul sound.
-
E.
Norman Gay
Norman Gay is a film editor best known for his work on the classic horror movie "The Exorcist."
- 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: Norman Grant Triple: [Space (novel), hasFictionalCharacter, Norman Grant]
Generated description
Norman Grant is a fictional character from the science fiction novel "Space" by James A. Michener.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Norman Grant Target entity description: Norman Grant is a fictional character from the science fiction novel "Space" by James A. Michener.
-
A.
Norman Clyde
Norman Clyde was a renowned American mountaineer and climber famed for his prolific first ascents and exploration of the Sierra Nevada.
-
B.
Norman Riley
Norman Riley is a distinguished mathematician and fluid dynamicist recognized for his influential contributions to theoretical and applied fluid mechanics.
-
C.
Norman Ferguson
Norman Ferguson was an American animator and film director at Walt Disney Studios, best known for his influential work on classic Disney features during the Golden Age of animation.
-
D.
Norman Harris
Norman Harris was an American soul and disco guitarist, songwriter, and producer closely associated with the Philadelphia soul sound.
-
E.
Norman Gay
Norman Gay is a film editor best known for his work on the classic horror movie "The Exorcist."
- 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_69d381ae26c48190985abd0e25ee5d04 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d395fbed008190b66996f5bb397853 |
completed | April 6, 2026, 11:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6a7f6730081908b941eaeb6c00993 |
completed | April 8, 2026, 7:09 p.m. |
| NEDg | Description generation | batch_69d6ad94a6a881908d4c3b4408695d5b |
completed | April 8, 2026, 7:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d6d02015bc8190a7041a7d725c8a1b |
completed | April 8, 2026, 10:01 p.m. |
Created at: April 6, 2026, 11:01 a.m.