Triple
T11907792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dinosaur (2000 film) |
E283314
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Eema
Eema is a wise, elderly Styracosaurus who serves as a gruff but good-hearted mentor figure in Disney's 2000 animated film "Dinosaur."
|
E953972
|
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: Eema | Statement: [Dinosaur (2000 film), mainCharacter, Eema]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eema Context triple: [Dinosaur (2000 film), mainCharacter, Eema]
-
A.
Taysir
Taysir is an Arabic male given name meaning "facilitation" or "making things easier," commonly used across the Arab world.
-
B.
Zahwa
Zahwa is a feminine given name of Arabic origin, often interpreted to mean "radiance" or "beauty."
-
C.
Sawila
Sawila is a Papuan language spoken on Alor Island in eastern Indonesia, known for its complex verb morphology and membership in the Alor–Pantar language family.
-
D.
Ema
Ema is a given name used as a variant spelling of Emma in various languages and cultures.
-
E.
Ema
Ema is an Austronesian language spoken primarily in East Timor, also known as the Kemak language.
- 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: Eema Triple: [Dinosaur (2000 film), mainCharacter, Eema]
Generated description
Eema is a wise, elderly Styracosaurus who serves as a gruff but good-hearted mentor figure in Disney's 2000 animated film "Dinosaur."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Eema Target entity description: Eema is a wise, elderly Styracosaurus who serves as a gruff but good-hearted mentor figure in Disney's 2000 animated film "Dinosaur."
-
A.
Taysir
Taysir is an Arabic male given name meaning "facilitation" or "making things easier," commonly used across the Arab world.
-
B.
Zahwa
Zahwa is a feminine given name of Arabic origin, often interpreted to mean "radiance" or "beauty."
-
C.
Sawila
Sawila is a Papuan language spoken on Alor Island in eastern Indonesia, known for its complex verb morphology and membership in the Alor–Pantar language family.
-
D.
Ema
Ema is a given name used as a variant spelling of Emma in various languages and cultures.
-
E.
Ema
Ema is an Austronesian language spoken primarily in East Timor, also known as the Kemak language.
- 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_69d6ab2c07e88190ba13b0d21fd6cf33 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8e5264b2081909bda6c24abb89725 |
completed | April 10, 2026, 11:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f418543258819083b49a5bbdc520cd |
completed | May 1, 2026, 3:04 a.m. |
| NEDg | Description generation | batch_69f41f1d2da0819082f00cf61a6530b6 |
completed | May 1, 2026, 3:33 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f4228a73708190a6d2db321e175921 |
completed | May 1, 2026, 3:48 a.m. |
Created at: April 8, 2026, 9:44 p.m.