Triple
T9802047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RealD 3D |
E237860
|
entity |
| Predicate | eyeSeparationMethod |
P90052
|
FINISHED |
| Object | alternating circular polarization |
—
|
LITERAL FINISHED |
How this triple was built (2 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: alternating circular polarization | Statement: [RealD 3D, eyeSeparationMethod, alternating circular polarization]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eyeSeparationMethod Context triple: [RealD 3D, eyeSeparationMethod, alternating circular polarization]
-
A.
eyeType
Indicates the specific kind or category of eyes an entity has, such as their form, structure, or visual style.
-
B.
eyeCount
Indicates the number of eyes an entity has.
-
C.
oculusDiameter
Indicates the diameter measurement of an oculus (a circular opening), relating the opening to the size of its circular span.
-
D.
eyeMigration
Indicates the movement or displacement of an eye (or eyes) from one position to another within an organism’s body or visual system.
-
E.
eyeCharacteristic
Indicates a relationship where an entity possesses a specific attribute, feature, or quality of its eyes.
- F. None of above. chosen
Provenance (4 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_69ca84dd4608819097ff4ed00feca280 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda62b41048190bcef70a7591830c6 |
completed | April 1, 2026, 11:11 p.m. |
| PD | Predicate disambiguation | batch_69cd03da45a88190b71b1be3354c15a6 |
completed | April 1, 2026, 11:39 a.m. |
| PDg | Predicate description generation | batch_69cd06abc9248190a506b64e9c516d03 |
completed | April 1, 2026, 11:51 a.m. |
Created at: March 30, 2026, 8:29 p.m.