Triple
T1748605
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thor (film) |
E38389
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object |
Jane Foster
Jane Foster is a brilliant astrophysicist and Thor’s primary human love interest in Marvel’s Thor films.
|
E197181
|
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: Jane Foster | Statement: [Thor (film), character, Jane Foster]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jane Foster Context triple: [Thor (film), character, Jane Foster]
-
A.
Sif
Sif is a goddess in Norse mythology best known as the golden-haired wife of Thor and a deity associated with earth, fertility, and grain.
-
B.
Hanna Lejonqvist
Hanna Lejonqvist is a film editor known for her work on the documentary "I Am Greta," which follows climate activist Greta Thunberg.
-
C.
Miss Quill
Miss Quill is a sharp-tongued, battle-hardened alien freedom fighter and teacher from the Doctor Who spin-off series "Class."
-
D.
Loki
Loki is a trickster god in Norse mythology known for his shape-shifting, cunning, and role in both aiding and undermining the other gods.
-
E.
Heimdall
Heimdall is a powerful Asgardian guardian in the Marvel universe, known for his all-seeing vision, immense strength, and duty to watch over the Bifröst Bridge.
- 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: Jane Foster Triple: [Thor (film), character, Jane Foster]
Generated description
Jane Foster is a brilliant astrophysicist and Thor’s primary human love interest in Marvel’s Thor films.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jane Foster Target entity description: Jane Foster is a brilliant astrophysicist and Thor’s primary human love interest in Marvel’s Thor films.
-
A.
Sif
Sif is a goddess in Norse mythology best known as the golden-haired wife of Thor and a deity associated with earth, fertility, and grain.
-
B.
Hanna Lejonqvist
Hanna Lejonqvist is a film editor known for her work on the documentary "I Am Greta," which follows climate activist Greta Thunberg.
-
C.
Miss Quill
Miss Quill is a sharp-tongued, battle-hardened alien freedom fighter and teacher from the Doctor Who spin-off series "Class."
-
D.
Loki
Loki is a trickster god in Norse mythology known for his shape-shifting, cunning, and role in both aiding and undermining the other gods.
-
E.
Heimdall
Heimdall is a powerful Asgardian guardian in the Marvel universe, known for his all-seeing vision, immense strength, and duty to watch over the Bifröst Bridge.
- 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_69a8862b01a48190ab47209063af82d9 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa63ee4d2081909dfd6d3244228c56 |
completed | March 6, 2026, 5:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ada0e21e58819082943212bd725581 |
completed | March 8, 2026, 4:16 p.m. |
| NEDg | Description generation | batch_69ada1a2fb9481909d9ed587921ca6b6 |
completed | March 8, 2026, 4:19 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ada4dfc9188190845a4e4490318d68 |
completed | March 8, 2026, 4:33 p.m. |
Created at: March 4, 2026, 7:31 p.m.