Triple
T5399217
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ingmar Bergman |
E120731
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Gun Grut
Gun Grut was a Swedish journalist and writer best known for being married to renowned film director Ingmar Bergman.
|
E517177
|
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: Gun Grut | Statement: [Ingmar Bergman, spouse, Gun Grut]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gun Grut Context triple: [Ingmar Bergman, spouse, Gun Grut]
-
A.
Gurgi
Gurgi is a timid yet loyal, creature-like companion character from Disney’s animated fantasy film "The Black Cauldron."
-
B.
Oger
Oger is a renowned Champagne-producing village in France’s Côte des Blancs, celebrated for its high-quality Chardonnay vineyards and prestigious Grand Cru status.
-
C.
Orco
The Orco is a river in northwestern Italy that flows through the Piedmont region and is a significant tributary of the Po.
-
D.
Tarasque
The Tarasque is a legendary dragon-like monster from Provençal folklore, famously tamed by Saint Martha and associated with the town of Tarascon in southern France.
-
E.
Smargadus
Smargadus was the exarch of Ravenna who commissioned the Column of Phocas in the Roman Forum in the early 7th century.
- 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: Gun Grut Triple: [Ingmar Bergman, spouse, Gun Grut]
Generated description
Gun Grut was a Swedish journalist and writer best known for being married to renowned film director Ingmar Bergman.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gun Grut Target entity description: Gun Grut was a Swedish journalist and writer best known for being married to renowned film director Ingmar Bergman.
-
A.
Gurgi
Gurgi is a timid yet loyal, creature-like companion character from Disney’s animated fantasy film "The Black Cauldron."
-
B.
Oger
Oger is a renowned Champagne-producing village in France’s Côte des Blancs, celebrated for its high-quality Chardonnay vineyards and prestigious Grand Cru status.
-
C.
Orco
The Orco is a river in northwestern Italy that flows through the Piedmont region and is a significant tributary of the Po.
-
D.
Tarasque
The Tarasque is a legendary dragon-like monster from Provençal folklore, famously tamed by Saint Martha and associated with the town of Tarascon in southern France.
-
E.
Smargadus
Smargadus was the exarch of Ravenna who commissioned the Column of Phocas in the Roman Forum in the early 7th century.
- 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_69bd4637b92c8190b815b6443ae4b323 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd87499ec4819086f8292625b56f96 |
completed | March 20, 2026, 5:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf337f08088190a3678de0932b8310 |
completed | March 22, 2026, 12:10 a.m. |
| NEDg | Description generation | batch_69bf353ad5f88190964cb52320372133 |
completed | March 22, 2026, 12:18 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69bf3594f98481909a7671b7dfb2b9e7 |
completed | March 22, 2026, 12:19 a.m. |
Created at: March 20, 2026, 2:04 p.m.